diff --git a/build/torch210-cu126-aarch64-linux/__init__.py b/build/torch210-cu126-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch210-cu126-aarch64-linux/_ops.py b/build/torch210-cu126-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch210-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch210-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..ab0deffff43b516d4af47b49a0100f368f2fbc5e
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6126ee8e7f7434e90d9f4011ef62630251f6ab8cc707a04ffcc0112226e6b7d
+size 6337928
diff --git a/build/torch210-cu126-aarch64-linux/layers.py b/build/torch210-cu126-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch210-cu126-aarch64-linux/metadata.json b/build/torch210-cu126-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..b0a1201bb48a903d0ae590bcd2e0ab9d58b5897c
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/metadata.json
@@ -0,0 +1,43 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "phJu6Of3Q06Q2fQBHvYmMCUfarjMcHoE/8wBEiJua30=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch210-cu126-aarch64-linux/metadata.json.sigstore b/build/torch210-cu126-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..5c00ff0c854d88dcf9281aaba47c79d62a29b793
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/metadata.json.sigstore
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\ No newline at end of file
diff --git a/build/torch210-cu126-aarch64-linux/symbols.json b/build/torch210-cu126-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch210-cu126-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch210-cu128-aarch64-linux/__init__.py b/build/torch210-cu128-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch210-cu128-aarch64-linux/_ops.py b/build/torch210-cu128-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch210-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch210-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..d602efad416e21ba6a444fef2d93e96cb83ab0f9
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40055e50c07700da6b9bf37330b1f465be0591256c2b5d6155dc7012cf2be10c
+size 10008872
diff --git a/build/torch210-cu128-aarch64-linux/layers.py b/build/torch210-cu128-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch210-cu128-aarch64-linux/metadata.json b/build/torch210-cu128-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ad074f3c4659a16b1acbc849ed068e299f57ef6
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "QAVeUMB3ANprm/NzMLH0Zb4FkSVsK11hVdxwEs8r4Qw=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch210-cu128-aarch64-linux/metadata.json.sigstore b/build/torch210-cu128-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..b86557b3b11e59f095255cf57efec9f02d402501
--- /dev/null
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diff --git a/build/torch210-cu128-aarch64-linux/symbols.json b/build/torch210-cu128-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch210-cu128-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch210-cu130-aarch64-linux/__init__.py b/build/torch210-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch210-cu130-aarch64-linux/_ops.py b/build/torch210-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch210-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch210-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..e38d156fdfb5b35a0cc2d29b7d5138aa25f92b52
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c7ac482809196a8c1b0dab0a93d63c375a37b434b377be6bdae749e528be74b3
+size 10957128
diff --git a/build/torch210-cu130-aarch64-linux/layers.py b/build/torch210-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch210-cu130-aarch64-linux/metadata.json b/build/torch210-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..aad355ea76fa633cc69ccb1de66ca44178e94f03
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "x6xIKAkZaowbDasKk9Y8N1o3tDSzd75r2udJ5Si+dLM=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch210-cu130-aarch64-linux/metadata.json.sigstore b/build/torch210-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..d6a2cf1a0e4fb5f9f216f78832681f8043efe7ba
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/metadata.json.sigstore
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diff --git a/build/torch210-cu130-aarch64-linux/symbols.json b/build/torch210-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch210-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch211-cu126-aarch64-linux/__init__.py b/build/torch211-cu126-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch211-cu126-aarch64-linux/_ops.py b/build/torch211-cu126-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch211-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch211-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..238e6157a9a47e3df7afa0f38ae2634fea299e46
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e45897fe4458a0ece9bf6dcc10f8bc399f3ce79397c626d0c559fd6560370174
+size 6334272
diff --git a/build/torch211-cu126-aarch64-linux/layers.py b/build/torch211-cu126-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch211-cu126-aarch64-linux/metadata.json b/build/torch211-cu126-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..2b9617f57239ad7136a6a16f09f6c6d22e34cc6f
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/metadata.json
@@ -0,0 +1,43 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "5FiX/kRYoOzpv23MEPi8OZ8855OXxibQxVn9ZWA3AXQ=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch211-cu126-aarch64-linux/metadata.json.sigstore b/build/torch211-cu126-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..48b7eb4cbab9d22fb1cac0eb5d41c30fa1084240
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\ No newline at end of file
diff --git a/build/torch211-cu126-aarch64-linux/symbols.json b/build/torch211-cu126-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch211-cu126-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch211-cu128-aarch64-linux/__init__.py b/build/torch211-cu128-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch211-cu128-aarch64-linux/_ops.py b/build/torch211-cu128-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch211-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch211-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..be8a5f63f9c71a9f0bd961967f5dcf2fea2a0625
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5e38b00686d0ad16a8b5ab4420f3279c16bcaa274306c14250c6f243c55e7a64
+size 10005216
diff --git a/build/torch211-cu128-aarch64-linux/layers.py b/build/torch211-cu128-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch211-cu128-aarch64-linux/metadata.json b/build/torch211-cu128-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..21d8eb64511d957d2d1eb1b7d637606f4882c881
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.1",
+      "12.0+PTX",
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "XjiwBobQrRaotatEIPMnnBa8qidDBsFCUMbyQ8VeemQ=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch211-cu128-aarch64-linux/metadata.json.sigstore b/build/torch211-cu128-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..6cef048973fc41b9700394221f9f1a6aab0ef6b7
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diff --git a/build/torch211-cu128-aarch64-linux/symbols.json b/build/torch211-cu128-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch211-cu128-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch211-cu130-aarch64-linux/__init__.py b/build/torch211-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch211-cu130-aarch64-linux/_ops.py b/build/torch211-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch211-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch211-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..55e05d5f8bda3eedeb83c46b2eb36ef9e85d58d4
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89eaea71556c106a178a3559987fbdd11372149ea145d9474f84c74cedd60dc5
+size 10953480
diff --git a/build/torch211-cu130-aarch64-linux/layers.py b/build/torch211-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch211-cu130-aarch64-linux/metadata.json b/build/torch211-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9c0b5a93836357cf83b4804f1a74d1e41891ff93
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "ierqcVVsEGoXijVZmH+90RNyFJ6hRdlHT4THTO3WDcU=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch211-cu130-aarch64-linux/metadata.json.sigstore b/build/torch211-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..749824af95bc77fbf1c23d327e032f99d62a12dd
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/metadata.json.sigstore
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diff --git a/build/torch211-cu130-aarch64-linux/symbols.json b/build/torch211-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch211-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch212-cu126-aarch64-linux/__init__.py b/build/torch212-cu126-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch212-cu126-aarch64-linux/_ops.py b/build/torch212-cu126-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch212-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch212-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..20568fcebf938115c91a4a1814da3cbe271d9dc3
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e004ec2d7ed554f0e1968df2ce3f50850190874b430d264c1f5f4d1b210bd122
+size 6337680
diff --git a/build/torch212-cu126-aarch64-linux/layers.py b/build/torch212-cu126-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch212-cu126-aarch64-linux/metadata.json b/build/torch212-cu126-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..dc4ddb03d481a5756017da327122fee3e1872a5d
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/metadata.json
@@ -0,0 +1,43 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "4ATsLX7VVPDhlo3yzj9QhQGQh0tDDSZMH19NGyEL0SI=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch212-cu126-aarch64-linux/metadata.json.sigstore b/build/torch212-cu126-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..32bddc90ba5830e1a6601d2ba27b8c04b525cce7
--- /dev/null
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diff --git a/build/torch212-cu126-aarch64-linux/symbols.json b/build/torch212-cu126-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch212-cu126-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch212-cu130-aarch64-linux/__init__.py b/build/torch212-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch212-cu130-aarch64-linux/_ops.py b/build/torch212-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch212-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch212-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..9153dda95f0556969b961ae5747edb36266b75f8
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d11f16530eb407cec9e558c47733cf3411de92934b83a89364d0fcce8b0b61a8
+size 10956776
diff --git a/build/torch212-cu130-aarch64-linux/layers.py b/build/torch212-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch212-cu130-aarch64-linux/metadata.json b/build/torch212-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..f293949223bdb7237ef9ff5216d1ec61f4e4be23
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "0R8WUw60B87J5VjEdzPPNBHekpNLg6iTZND8zosLYag=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch212-cu130-aarch64-linux/metadata.json.sigstore b/build/torch212-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..fe8138523f7a0b5a9c636079464c2a467fb910e3
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diff --git a/build/torch212-cu130-aarch64-linux/symbols.json b/build/torch212-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch212-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch212-cu132-aarch64-linux/__init__.py b/build/torch212-cu132-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch212-cu132-aarch64-linux/_ops.py b/build/torch212-cu132-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch212-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch212-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..9708e7d7f47eaa04828c920b5226a81fd0053319
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6968ef4f8f5336909f0c685cbdacdd022a923ba05a907d4c58072f59580527d
+size 11223552
diff --git a/build/torch212-cu132-aarch64-linux/layers.py b/build/torch212-cu132-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch212-cu132-aarch64-linux/metadata.json b/build/torch212-cu132-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..4853c8e9d3ecec53aa324efaa3fc5cb5bbfc5bcf
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "tpaO9Pj1M2kJ8MaFy9rN0CKpI7oFqQfUxYBy9ZWAUn0=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch212-cu132-aarch64-linux/metadata.json.sigstore b/build/torch212-cu132-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..0dd9f48d9dfc6628dcd14481ef9f9d6cc5d6bf94
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diff --git a/build/torch212-cu132-aarch64-linux/symbols.json b/build/torch212-cu132-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch212-cu132-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch213-cu126-aarch64-linux/__init__.py b/build/torch213-cu126-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch213-cu126-aarch64-linux/_ops.py b/build/torch213-cu126-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch213-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch213-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..915d8be643f6aef897fb134426e63daf04491a66
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a30be7e14efb9270f7591cdb3be7cc2bd7ef1a65fc7216d0d06bfcfcfefc4a4
+size 6337568
diff --git a/build/torch213-cu126-aarch64-linux/layers.py b/build/torch213-cu126-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch213-cu126-aarch64-linux/metadata.json b/build/torch213-cu126-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..14b27c2ad4f54f327c570e1e0bbbb7dffbbd23e0
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/metadata.json
@@ -0,0 +1,43 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "KjC+fhTvuScPdZHNs758wr1+8aZfxyFtDQa/z8/vxKQ=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch213-cu126-aarch64-linux/metadata.json.sigstore b/build/torch213-cu126-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..087cff7fa47da606c95d382b48e3f566cee83aef
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diff --git a/build/torch213-cu126-aarch64-linux/symbols.json b/build/torch213-cu126-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch213-cu126-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch213-cu130-aarch64-linux/__init__.py b/build/torch213-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch213-cu130-aarch64-linux/_ops.py b/build/torch213-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch213-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch213-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..a8f6ee2dfc52ba001d2ad915e6e9f709ac0d823c
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6a256ed8242032f5242a158d0880e60cf6968e44066c609604fce75de98d04cc
+size 10956664
diff --git a/build/torch213-cu130-aarch64-linux/layers.py b/build/torch213-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch213-cu130-aarch64-linux/metadata.json b/build/torch213-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..465ab6305a9452a06ef5847909b6fe71d912c074
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "aiVu2CQgMvUkKhWNCIDmDPaWjkQGbGCWBPznXemNBMw=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch213-cu130-aarch64-linux/metadata.json.sigstore b/build/torch213-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..2d4c56f70e689780a44732048e2992e97ee60bb1
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/metadata.json.sigstore
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diff --git a/build/torch213-cu130-aarch64-linux/symbols.json b/build/torch213-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch213-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch213-cu132-aarch64-linux/__init__.py b/build/torch213-cu132-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch213-cu132-aarch64-linux/_ops.py b/build/torch213-cu132-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch213-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch213-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..b4e5959594490afc1dbc640e62a50baf00b3afe1
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fa4cd9826a05cb683b8c37b5d2664330474ee4c4f227d082ca89a25894f2943d
+size 11223440
diff --git a/build/torch213-cu132-aarch64-linux/layers.py b/build/torch213-cu132-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch213-cu132-aarch64-linux/metadata.json b/build/torch213-cu132-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..1a5128d1285794b3c0a233044c0d9fb3945bc156
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "+kzZgmoFy2g7jDe10mZDMEdO5MTyJ9CCyomiWJTylD0=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch213-cu132-aarch64-linux/metadata.json.sigstore b/build/torch213-cu132-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..6fed2f59970e51008cc6af200e7ac4dc017a9715
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diff --git a/build/torch213-cu132-aarch64-linux/symbols.json b/build/torch213-cu132-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch213-cu132-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch214-cu126-aarch64-linux/__init__.py b/build/torch214-cu126-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch214-cu126-aarch64-linux/_ops.py b/build/torch214-cu126-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch214-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch214-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..0bc8516f7803638ebde0f2a190b0992f8f910cd6
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7399e3454d71b5454df9e23cd0c257619d0bee3befcbd42db3fe453e03bb4259
+size 6338320
diff --git a/build/torch214-cu126-aarch64-linux/layers.py b/build/torch214-cu126-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch214-cu126-aarch64-linux/metadata.json b/build/torch214-cu126-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..85bb0bcc50fb227e4f03ce86eaa633f91a74e075
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/metadata.json
@@ -0,0 +1,43 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "7.0",
+      "7.2",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0+PTX"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "c5njRU1xtUVN+eI80MJXYZ0L7jvvy9Qts/5FPgO7Qlk=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch214-cu126-aarch64-linux/metadata.json.sigstore b/build/torch214-cu126-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..7b619b773b7bdbb368044d53a776f3a5112f1296
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diff --git a/build/torch214-cu126-aarch64-linux/symbols.json b/build/torch214-cu126-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch214-cu126-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch214-cu130-aarch64-linux/__init__.py b/build/torch214-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch214-cu130-aarch64-linux/_ops.py b/build/torch214-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch214-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch214-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..e3090f571685410208fa5d856a76563fb82ecce1
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e26e78ad239df2b8c97af540c266783a57304bf2b5c5da6a81c8a8268ce75de
+size 10957424
diff --git a/build/torch214-cu130-aarch64-linux/layers.py b/build/torch214-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch214-cu130-aarch64-linux/metadata.json b/build/torch214-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..c9809ae9e4041fd74c12cf06d774ae6b227e927e
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "DibnitI53yuMl69UDCZng6VzBL8rXF2mqByKgmjOdd4=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch214-cu130-aarch64-linux/metadata.json.sigstore b/build/torch214-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..fbbb85c74a2734da6a0c65ab75f026d648159bca
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+++ b/build/torch214-cu130-aarch64-linux/metadata.json.sigstore
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diff --git a/build/torch214-cu130-aarch64-linux/symbols.json b/build/torch214-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch214-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch214-cu132-aarch64-linux/__init__.py b/build/torch214-cu132-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch214-cu132-aarch64-linux/_ops.py b/build/torch214-cu132-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch214-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch214-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..98cc258d3e27fd2055088113c0e190318810cda6
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a341decc468d71940f7c9845a9eb9114520040da36f7bdc78d21685c789af508
+size 11224192
diff --git a/build/torch214-cu132-aarch64-linux/layers.py b/build/torch214-cu132-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch214-cu132-aarch64-linux/metadata.json b/build/torch214-cu132-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..0bef80e149a5e03e7bc66db14672f4f2eba899bf
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "o0HezEaNcZQPfJhFqeuRFFIAQNo2973HjSFoXHia9Qg=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch214-cu132-aarch64-linux/metadata.json.sigstore b/build/torch214-cu132-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..e966e4edc729f49e851f0c663b124a3e63e36f21
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diff --git a/build/torch214-cu132-aarch64-linux/symbols.json b/build/torch214-cu132-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch214-cu132-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch215-cu130-aarch64-linux/__init__.py b/build/torch215-cu130-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch215-cu130-aarch64-linux/_ops.py b/build/torch215-cu130-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch215-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch215-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..90f15612e7b93f111819c593983a6ce11b84103a
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:54431867599387c901a0c96383aea4ae1d1e85a9bc7108ad51fd0889b1eee5c5
+size 10957424
diff --git a/build/torch215-cu130-aarch64-linux/layers.py b/build/torch215-cu130-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch215-cu130-aarch64-linux/metadata.json b/build/torch215-cu130-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..2c4f87e5ea8b420c974e6afc19f1f29342525c32
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "VEMYZ1mTh8kBoMljg66krh0eham8cQitUf0IibHu5cU=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch215-cu130-aarch64-linux/metadata.json.sigstore b/build/torch215-cu130-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..459af6432c2521201c9cbc8c50efb6a9ff7d8875
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/metadata.json.sigstore
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\ No newline at end of file
diff --git a/build/torch215-cu130-aarch64-linux/symbols.json b/build/torch215-cu130-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch215-cu130-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch215-cu132-aarch64-linux/__init__.py b/build/torch215-cu132-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch215-cu132-aarch64-linux/_ops.py b/build/torch215-cu132-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch215-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch215-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..af1f2dc399b43f2d8c5527466248ef3cfe620b05
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d3840a79f43b8759a589f001aeb1a936d00bf887e9abf66de5f7989cf6b027c0
+size 11224192
diff --git a/build/torch215-cu132-aarch64-linux/layers.py b/build/torch215-cu132-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch215-cu132-aarch64-linux/metadata.json b/build/torch215-cu132-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..caa7c8743be15a9e65c4f89a026f2eeabef26d6e
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "04QKefQ7h1mlifABrrGpNtAL+Ifpq/Zt5feYnPawJ8A=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch215-cu132-aarch64-linux/metadata.json.sigstore b/build/torch215-cu132-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..f2abfcf754802402d94154c04d15a2d999e34e21
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diff --git a/build/torch215-cu132-aarch64-linux/symbols.json b/build/torch215-cu132-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch215-cu132-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}
diff --git a/build/torch215-cu134-aarch64-linux/__init__.py b/build/torch215-cu134-aarch64-linux/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4ae5eb764bfd4529302f6ebd55a63cfc4290248
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/__init__.py
@@ -0,0 +1,57 @@
+import torch
+
+from . import layers
+from ._ops import ops
+
+
+def apply_rotary(
+    x1: torch.Tensor,
+    x2: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    out1: torch.Tensor,
+    out2: torch.Tensor,
+    conj: bool,
+) -> None:
+    ops.apply_rotary(x1, x2, cos, sin, out1, out2, conj)
+
+
+def apply_rotary_transformers(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    cos: torch.Tensor,
+    sin: torch.Tensor,
+    unsqueeze_dim: int = 1,
+) -> tuple[torch.Tensor, torch.Tensor]:
+    """
+    Rotary kernel implementation wrapper
+    Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+    """
+    cos = cos.unsqueeze(unsqueeze_dim)
+    sin = sin.unsqueeze(unsqueeze_dim)
+
+    q_rotated = q.clone()
+    k_rotated = k.clone()
+
+    # Get half dimension for rotation
+    half_dim = q.shape[-1] // 2
+    q1 = q_rotated[..., :half_dim]
+    q2 = q_rotated[..., half_dim:]
+    k1 = k_rotated[..., :half_dim]
+    k2 = k_rotated[..., half_dim:]
+    if cos.shape[-1] != half_dim:
+        # Trim cos/sin to match half_dim
+        cos = cos[..., :half_dim]
+        sin = sin[..., :half_dim]
+
+    apply_rotary(q1, q2, cos, sin, q1, q2, False)
+    apply_rotary(k1, k2, cos, sin, k1, k2, False)
+    return q_rotated, k_rotated
+
+
+# Add torch compile support for functions
+apply_rotary_transformers.can_torch_compile = True
+
+
+# Keeping `apply_rotary` and `apply_rotary_transformers` for BC
+__all__ = ["apply_rotary", "apply_rotary_transformers", "layers"]
diff --git a/build/torch215-cu134-aarch64-linux/_ops.py b/build/torch215-cu134-aarch64-linux/_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e9d695ead35d31082b675c39d2a8bc2bb2e203b
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/_ops.py
@@ -0,0 +1,9 @@
+import torch
+from . import _rotary_cuda_fe2bb66
+ops = torch.ops._rotary_cuda_fe2bb66
+
+def add_op_namespace_prefix(op_name: str):
+    """
+    Prefix op by namespace.
+    """
+    return f"_rotary_cuda_fe2bb66::{op_name}"
diff --git a/build/torch215-cu134-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so b/build/torch215-cu134-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
new file mode 100644
index 0000000000000000000000000000000000000000..2bda3e5dc8855832befcb746d80baa9d51a0432e
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/_rotary_cuda_fe2bb66.abi3.so
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3bf6b366bc168ec01e99e061cb033b9ed6659a4f64ac8d7ec43f58359bc03022
+size 11092056
diff --git a/build/torch215-cu134-aarch64-linux/layers.py b/build/torch215-cu134-aarch64-linux/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..ac7d829334e10090a3190775b8ae51f739501512
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/layers.py
@@ -0,0 +1,41 @@
+import torch
+import torch.nn as nn
+
+from ._ops import ops
+
+
+class apply_rotary_transformers(nn.Module):
+    can_torch_compile = True
+
+    def forward(
+        self,
+        q: torch.Tensor,
+        k: torch.Tensor,
+        cos: torch.Tensor,
+        sin: torch.Tensor,
+        unsqueeze_dim: int = 1,
+    ) -> tuple[torch.Tensor, torch.Tensor]:
+        """
+        Rotary kernel implementation wrapper
+        Adapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature
+        """
+        cos = cos.unsqueeze(unsqueeze_dim)
+        sin = sin.unsqueeze(unsqueeze_dim)
+
+        q_rotated = q.clone()
+        k_rotated = k.clone()
+
+        # Get half dimension for rotation
+        half_dim = q.shape[-1] // 2
+        q1 = q_rotated[..., :half_dim]
+        q2 = q_rotated[..., half_dim:]
+        k1 = k_rotated[..., :half_dim]
+        k2 = k_rotated[..., half_dim:]
+        if cos.shape[-1] != half_dim:
+            # Trim cos/sin to match half_dim
+            cos = cos[..., :half_dim]
+            sin = sin[..., :half_dim]
+
+        ops.apply_rotary(q1, q2, cos, sin, q1, q2, False)
+        ops.apply_rotary(k1, k2, cos, sin, k1, k2, False)
+        return q_rotated, k_rotated
diff --git a/build/torch215-cu134-aarch64-linux/metadata.json b/build/torch215-cu134-aarch64-linux/metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..9b7f9344d52a79dc4a832e8e3b887472f6be558e
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/metadata.json
@@ -0,0 +1,46 @@
+{
+  "name": "rotary",
+  "id": "_rotary_cuda_fe2bb66",
+  "version": 2,
+  "kernels-minver": "0.14.0",
+  "license": "BSD-3-Clause",
+  "python-depends": [],
+  "kernel-depends": [],
+  "backend": {
+    "type": "cuda",
+    "archs": [
+      "10.0",
+      "10.3",
+      "11.0",
+      "12.0",
+      "12.1+PTX",
+      "7.5",
+      "8.0",
+      "8.6",
+      "8.7",
+      "8.9",
+      "9.0"
+    ]
+  },
+  "digest": {
+    "algorithm": "sha256",
+    "files": {
+      "__init__.py": "qlvCb0Z6KMkcCxgjDRxjD1ofWaJ/Lqx0cTFlqrncWyE=",
+      "_ops.py": "EoWScriRucWeQpTCVjU8Plvxj4hCleb78Xs7ZS54SEo=",
+      "_rotary_cuda_fe2bb66.abi3.so": "O/azZrwWjsAemeBhywM7ntZlmk9krI1+xD9YNZvAMCI=",
+      "layers.py": "c8ZzUlsVi1lOGhM67JSViZdKBSbIKItQxmWkXPiTEy4=",
+      "symbols.json": "zKJ3WtDUryzwwEOaYEkFFuht8M+29N2RldN2OP/+GuM="
+    }
+  },
+  "provenance": {
+    "kernel-builder": {
+      "version": "0.18.0-dev0",
+      "commit": "d054906a13710b811b96697b4635f03020842733",
+      "dirty": false
+    },
+    "kernel": {
+      "commit": "fe2bb66fee6c2a77eccf08a0508dc57428d488ed",
+      "dirty": false
+    }
+  }
+}
\ No newline at end of file
diff --git a/build/torch215-cu134-aarch64-linux/metadata.json.sigstore b/build/torch215-cu134-aarch64-linux/metadata.json.sigstore
new file mode 100644
index 0000000000000000000000000000000000000000..f7076f96d81267d28158d9411cf3cefe49c09b38
--- /dev/null
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diff --git a/build/torch215-cu134-aarch64-linux/symbols.json b/build/torch215-cu134-aarch64-linux/symbols.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f0fcc334041d0c5bb198ce5cb30981058ba4b31
--- /dev/null
+++ b/build/torch215-cu134-aarch64-linux/symbols.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "module": "_rotary_cuda_fe2bb66",
+  "functions": [
+    {
+      "name": "apply_rotary",
+      "qualname": "apply_rotary",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": null,
+      "signature": {
+        "parameters": [
+          {
+            "name": "x1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "x2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out1",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "out2",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "conj",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "bool"
+          }
+        ],
+        "return_annotation": "None"
+      }
+    },
+    {
+      "name": "apply_rotary_transformers",
+      "qualname": "apply_rotary_transformers",
+      "module": "_rotary_cuda_fe2bb66",
+      "kind": "function",
+      "doc": "Rotary kernel implementation wrapper\nAdapts rotary kernel implementation to match transformers apply_rotary_pos_emb signature",
+      "signature": {
+        "parameters": [
+          {
+            "name": "q",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "k",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "cos",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "sin",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": null,
+            "annotation": "torch.Tensor"
+          },
+          {
+            "name": "unsqueeze_dim",
+            "kind": "POSITIONAL_OR_KEYWORD",
+            "default": "1",
+            "annotation": "int"
+          }
+        ],
+        "return_annotation": "tuple[torch.Tensor, torch.Tensor]"
+      }
+    }
+  ],
+  "layers": []
+}