Publish one FP32 safetensors checkpoint with native usage instructions

NOTICE

@@ -0,0 +1,9 @@
+Original publisher: HengruiTianSJTU
+Native MLX conversion: MedMLX; tensor layout/storage conversion without retraining.
+Private research archive. Original checkpoint and component terms remain applicable.
+This archive does not grant a new or broader license.
+
+Retain the applicable license, copyright and attribution notices; identify the upstream checkpoint, authors, and MLX conversion changes.
+
+Publisher and license sources:
+https://github.com/HengruiTianSJTU/LesionDiffusion

README.md

@@ -6,8 +6,7 @@ tags:
 - apple-silicon
 - research
 - inference
-- conversion
-- model-card-only
+- safetensors
 language:
 - en
 license_name: upstream-component-terms
@@ -19,7 +18,7 @@ pipeline_tag: image-to-image
 
 Native MLX LesionDiffusion synthesis on Apple Silicon using LMNet, LINet, and VQ components. The recorded paper configuration inserts a liver tumor into a prepared CT crop; current conditioned inference is documented separately below.
 
-**Repository contents:** model card and local conversion instructions. No checkpoint, tokenizer, medical image, or output data is included. Obtain original assets directly from their publishers under the applicable terms.
+**Repository contents:** converted FP32 safetensors weights, runtime JSON metadata where required, and retained publisher notices. This repository is private; original checkpoint and component terms remain applicable.
 
 Requires an Apple Silicon Mac with Metal and Python 3.12/3.13. Model inference uses MLX; PyTorch is used for one-time checkpoint conversion and optional upstream comparisons. Intended for research and education; clinical diagnostic performance has not been established.
 
@@ -38,7 +37,26 @@ Original checkpoint: Component locations are in the native run record and the up
 Conversion: lesiondiffusion_mlx.write_conversion (README recipe), using the upstream component checkpoints and an explicitly supplied BiomedCLIP tokenizer.
 Conversion changes tensor layout or storage as specified by the native package; it does not retrain the model.
 
-## Install and convert
+## Download the safetensors bundle
+
+Authenticate as a member of MedMLX, then download the private repository:
+
+```bash
+hf download MedMLX/lesiondiffusion-mlx --local-dir lesiondiffusion
+```
+
+The current source checkout needs the included safetensors loader patch. The patch changes serialization support only; the existing local NPZ input contract is retained. Install the pinned source with that patch:
+
+```bash
+git clone https://github.com/MedMLX/lesiondiffusion-mlx.git lesiondiffusion-mlx-source
+git -C lesiondiffusion-mlx-source checkout c8cac6e616895618254069bcf10ddf292409bc62
+git -C lesiondiffusion-mlx-source apply ../lesiondiffusion/safetensors-support.patch
+uv pip install ./lesiondiffusion-mlx-source
+```
+
+The recorded usage example below uses this bundle. The original conversion recipe is retained for reproducibility.
+
+## Reproduce the upstream conversion (optional)
 
 Install the native package with conversion support:
 
@@ -106,9 +124,9 @@ The current package defaults to `inference_mode="conditioned"`, which enables LI
 ## Distribution terms
 
 Upstream code: **MIT**. Weights: **Unresolved; retrieve directly from the original publisher**.
-Eligible route: **converter**. Prepared locally; no converted weights uploaded.
+Distribution: **private converted-weight archive**. Public redistribution review remains separate; the original component terms are unchanged.
 
-Full controlled 200-step paired reference completed October 12; image cosine 0.99996977 and lesion Dice 1.0. Density and outside-lesion reconstruction limitations remain. No unambiguous complete-component redistribution grant verified; distribute conversion code and refer users to the original weights.
+Full controlled 200-step paired reference completed October 12; image cosine 0.99996977 and lesion Dice 1.0. Density and outside-lesion reconstruction limitations remain. The complete component terms have not been cleared for public redistribution.
 
 Required notices:
 
@@ -117,3 +135,11 @@ Required notices:
 Review sources:
 
 - https://github.com/HengruiTianSJTU/LesionDiffusion
+
+## Packaged weights
+
+Exactly one safetensors file contains the converted FP32 weights. JSON files are required runtime metadata or tokenizer assets. This upload does not rerun or extend the recorded model qualification.
+
+- `model.safetensors` (1,665,997,956 bytes)
+
+Component names prefix tensor keys in `model.safetensors`; the included loader patch selects each component without changing its values or precision.

SOURCE_LICENSE

@@ -0,0 +1,202 @@
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conversion.json

@@ -0,0 +1,33 @@
+{
+  "schema_version": "medmlx.lesiondiffusion.weights.v1",
+  "converter_version": 1,
+  "source_ref": "880736e2b8a4d9becdb6594da7f8af6db19d04d1",
+  "layout": "source_torch_ncdhw",
+  "stored_dtype": "float32",
+  "inference_dtype": {
+    "lmnet": "float32",
+    "linet": "float16",
+    "vq": "float16"
+  },
+  "ema": true,
+  "source_files": {
+    "LMNet.ckpt": {},
+    "LINet.ckpt": {},
+    "VQ.ckpt": {}
+  },
+  "converted_files": {
+    "lmnet.npz": {},
+    "linet.npz": {},
+    "vq.npz": {},
+    "lmnet_text.npz": {},
+    "linet_text.npz": {}
+  },
+  "tensor_file": "model.safetensors",
+  "tensor_prefixes": {
+    "linet": "linet.",
+    "linet_text": "linet_text.",
+    "lmnet": "lmnet.",
+    "lmnet_text": "lmnet_text.",
+    "vq": "vq."
+  }
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11da7d80af556d6fbc08efe2da828ebe37a226be22e3a7bde2168a68158c0201
+size 1665997956

safetensors-support.patch

@@ -0,0 +1,130 @@
+diff --git a/pyproject.toml b/pyproject.toml
+index bbaab24..e3e0534 100644
+--- a/pyproject.toml
++++ b/pyproject.toml
+@@ -20,6 +20,7 @@ dependencies = [
+   "medmlx-core @ git+https://github.com/MedMLX/medmlx-core.git@0a83421597991ad04c76a532780273c13854cbac",
+   "nibabel>=5.3,<6",
+   "numpy>=2.0,<3",
++  "safetensors>=0.6,<1",
+   "scipy>=1.15,<2",
+   "tokenizers>=0.21,<1",
+ ]
+diff --git a/src/lesiondiffusion_mlx/medmlx.py b/src/lesiondiffusion_mlx/medmlx.py
+index 6dfc21a..e8ec266 100644
+--- a/src/lesiondiffusion_mlx/medmlx.py
++++ b/src/lesiondiffusion_mlx/medmlx.py
+@@ -69,7 +69,7 @@ WARNING: Final = (
+ )
+ WEIGHTS_HINT: Final = (
+     "Convert explicit upstream checkpoints with scripts/convert_weights.py; "
+-    "weights_path must contain the NPZ stages, tokenizer.json and conversion.json."
++    "weights_path must contain safetensors or NPZ stages, tokenizer.json and conversion.json."
+ )
+ 
+ # Canonical labels match upstream organ_type.json and its inference vocabulary.
+@@ -776,6 +776,12 @@ def source_organ_label(organ: str) -> tuple[int, str]:
+ # --- converted weights ----------------------------------------------------------------
+ 
+ 
++def _stage_file(directory: Path, name: str) -> Path:
++    """Use the consolidated release or an existing local NPZ conversion."""
++    path = directory / "model.safetensors"
++    return path if path.is_file() else directory / (name + ".npz")
++
++
+ def require_weights(path: _PathArg, *, inference_mode: str = DEFAULT_INFERENCE_MODE) -> Path:
+     """Require a self-contained, current conversion."""
+ 
+@@ -787,17 +793,29 @@ def require_weights(path: _PathArg, *, inference_mode: str = DEFAULT_INFERENCE_M
+             hint=WEIGHTS_HINT,
+         )
+     inference_files = SOURCE_INFERENCE_FILES if inference_mode == "source" else CONVERTED_FILES
+-    missing = [
+-        directory / name
+-        for name in (*inference_files, TOKENIZER_FILE, CONVERSION_FILE)
+-        if not (directory / name).is_file()
+-    ]
++    files = [_stage_file(directory, Path(name).stem) for name in inference_files]
++    files.extend((directory / TOKENIZER_FILE, directory / CONVERSION_FILE))
++    missing = [file for file in files if not file.is_file()]
+     if missing:
+         raise AssetNotReadyError(
+             f"Native MLX LesionDiffusion weights are not ready: missing {missing[0]}",
+             reason=f"Missing native LesionDiffusion asset: {missing[0]}",
+             hint=WEIGHTS_HINT,
+         )
++    packed = directory / "model.safetensors"
++    if packed.is_file():
++        from safetensors import safe_open
++
++        with safe_open(packed, framework="np") as tensors:
++            names = tensors.keys()
++            present = {key.split(".", 1)[0] for key in names}
++        for name in inference_files:
++            if Path(name).stem not in present:
++                raise AssetNotReadyError(
++                    f"Native MLX LesionDiffusion weights are missing stage {Path(name).stem}",
++                    reason=f"Missing stage in {packed.name}",
++                    hint=WEIGHTS_HINT,
++                )
+     try:
+         load_conversion(directory)
+     except (ValueError, OSError) as exc:
+@@ -843,8 +861,15 @@ def load_conversion(directory: Path) -> dict[str, object]:
+ def load_stage(directory: Path, name: str, mx: Mlx, *, dtype: Dtype) -> dict[str, Array]:
+     """Load converted arrays and copy them to the MLX device."""
+     load_conversion(directory)
+-    path = directory / (name + ".npz")
++    path = _stage_file(directory, name)
+     loaded = mx.load(str(path))
++    if path.name == "model.safetensors":
++        prefix = name + "."
++        return {
++            key.removeprefix(prefix): value.astype(dtype)
++            for key, value in loaded.items()
++            if key.startswith(prefix)
++        }
+     return {key: value.astype(dtype) for key, value in loaded.items()}
+ 
+ 
+diff --git a/uv.lock b/uv.lock
+index 708012c..63dc443 100644
+--- a/uv.lock
++++ b/uv.lock
+@@ -200,6 +200,7 @@ dependencies = [
+     { name = "medmlx-core" },
+     { name = "nibabel" },
+     { name = "numpy" },
++    { name = "safetensors" },
+     { name = "scipy" },
+     { name = "tokenizers" },
+ ]
+@@ -237,6 +238,7 @@ requires-dist = [
+     { name = "pyright", extras = ["nodejs"], marker = "extra == 'dev'", specifier = "==1.1.414" },
+     { name = "pytest", marker = "extra == 'dev'", specifier = ">=8.4,<10" },
+     { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.13,<1" },
++    { name = "safetensors", specifier = ">=0.6,<1" },
+     { name = "scipy", specifier = ">=1.15,<2" },
+     { name = "scipy-stubs", marker = "extra == 'dev'", specifier = ">=1.18.1.1,<1.19" },
+     { name = "tokenizers", specifier = ">=0.21,<1" },
+diff --git a/typings/safetensors/__init__.pyi b/typings/safetensors/__init__.pyi
+new file mode 100644
+index 0000000..fcfb957
+--- /dev/null
++++ b/typings/safetensors/__init__.pyi
+@@ -0,0 +1,14 @@
++from os import PathLike
++from types import TracebackType
++from typing import Self
++
++class safe_open:
++    def __init__(self, filename: str | PathLike[str], framework: str) -> None: ...
++    def __enter__(self) -> Self: ...
++    def __exit__(
++        self,
++        exc_type: type[BaseException] | None,
++        exc_value: BaseException | None,
++        traceback: TracebackType | None,
++    ) -> None: ...
++    def keys(self) -> list[str]: ...