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{
  "format": 1,
  "base_model": {
    "repo": "TencentARC/Pixal3D",
    "revision": "0b31f9160aa400719af409098bff7936a932f726"
  },
  "key_convention": "Each key is 'backbone.model.<path>.lora_A.weight' or 'backbone.model.<path>.lora_B.weight', where <path> names an nn.Linear in the state dict of the base flow model given by base_submodel (minus its '.weight' suffix); lora_A has shape [rank, in_features], lora_B has shape [out_features, rank], and the layer's weight update is (alpha / rank) * lora_B @ lora_A; example: 'backbone.model.blocks.0.self_attn.to_qkv.lora_A.weight'.",
  "fold_rule": {
    "none": "The adapters stay separate in float32: y = base(x) + (lora_B(lora_A(x.float())) * (alpha / rank)).to(base(x).dtype).",
    "bf16": "At load time each adapted weight W (bfloat16, the dtype of the base model's transformer blocks) is replaced by W + ((lora_B.float() @ lora_A.float()) * (alpha / rank)).to(bfloat16), the sum being taken in bfloat16, and the adapters are removed."
  },
  "students": {
    "structure": {
      "file": "structure_student.safetensors",
      "sha256": "a938130271c96eaaf67643bb428aa2aa8e53033b09608ea3eedc5531d9b97396",
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      "pipeline_key": "sparse_structure_flow_model",
      "lora": {
        "rank": 256,
        "alpha": 256,
        "target_modules": [
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          "cross_attn.cross_attn_block.to_kv",
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          "cross_attn.proj_linear",
          "mlp.mlp.0",
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        "num_blocks": 30,
        "num_adapters": 240,
        "num_tensors": 480,
        "num_elements": 318504960
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      "steps": {
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        "t": [
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          0.6,
          0.0
        ],
        "grid_indices": [
          0,
          3,
          6,
          8,
          12
        ],
        "teacher_grid": "t = linspace(1, 0, 13) warped by t' = 3t / (1 + 2t); grid_indices index this grid",
        "update": "euler",
        "guidance_strength": 1.0
      },
      "fold": "none",
      "dtype": "float32",
      "source_checkpoint_sha256": "be04198a3751c999343510611e627ff92a696b02bdeb83ec8ea93c966663c1f8",
      "training_updates": 500
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    "coarse_shape": {
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      "size_bytes": 1305542328,
      "base_submodel": "ckpts/slat_flow_img2shape_dit_1_3B_512_bf16",
      "pipeline_key": "shape_slat_flow_model_512",
      "lora": {
        "rank": 256,
        "alpha": 256,
        "target_modules": [
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          "self_attn.to_out",
          "cross_attn.cross_attn_block.to_q",
          "cross_attn.cross_attn_block.to_kv",
          "cross_attn.cross_attn_block.to_out",
          "cross_attn.proj_linear",
          "mlp.mlp.0",
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        "num_blocks": 30,
        "num_adapters": 240,
        "num_tensors": 480,
        "num_elements": 326369280
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      "steps": {
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        "t": [
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        ],
        "update": "x0_prediction",
        "guidance_strength": 1.0,
        "x0_formula": "x0 = (1 - s) * x_t - (s + (1 - s) * t) * v with s = 1e-5, in float64"
      },
      "fold": "none",
      "dtype": "float32",
      "source_checkpoint_sha256": "46bc526388cc55f226d5747e64d7cd8a32fbe9153fdd0ff67eac7695ed148e1f",
      "training_updates": 3000
    },
    "fine_shape": {
      "file": "fine_shape_student.safetensors",
      "sha256": "6beb37c82f5f618f84d9bc988564d41e3971ff85c42ef06217e580186e7dd583",
      "size_bytes": 1305542328,
      "base_submodel": "ckpts/slat_flow_img2shape_dit_1_3B_1024_bf16",
      "pipeline_key": "shape_slat_flow_model_1024",
      "lora": {
        "rank": 256,
        "alpha": 256,
        "target_modules": [
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          "self_attn.to_out",
          "cross_attn.cross_attn_block.to_q",
          "cross_attn.cross_attn_block.to_kv",
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          "cross_attn.proj_linear",
          "mlp.mlp.0",
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        "num_adapters": 240,
        "num_tensors": 480,
        "num_elements": 326369280
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      "steps": {
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        "t": [
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          0.0
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        "update": "x0_prediction",
        "guidance_strength": 1.0,
        "x0_formula": "x0 = (1 - s) * x_t - (s + (1 - s) * t) * v with s = 1e-5, in float64"
      },
      "fold": "bf16",
      "dtype": "float32",
      "source_checkpoint_sha256": "9fa67dd330e2dcfaf751e281d19ed8cc3e9c949c97a1a0d0d1a5940bafda070c",
      "training_updates": 2000
    },
    "texture": {
      "file": "texture_student.safetensors",
      "sha256": "ecc4ae096358120cde9ef2a6bbdff8bfee5c04e5f3bc49db84183d0f7d37887c",
      "size_bytes": 1305542328,
      "base_submodel": "ckpts/slat_flow_imgshape2tex_dit_1_3B_1024_bf16",
      "pipeline_key": "tex_slat_flow_model_1024",
      "lora": {
        "rank": 256,
        "alpha": 256,
        "target_modules": [
          "self_attn.to_qkv",
          "self_attn.to_out",
          "cross_attn.cross_attn_block.to_q",
          "cross_attn.cross_attn_block.to_kv",
          "cross_attn.cross_attn_block.to_out",
          "cross_attn.proj_linear",
          "mlp.mlp.0",
          "mlp.mlp.2"
        ],
        "num_blocks": 30,
        "num_adapters": 240,
        "num_tensors": 480,
        "num_elements": 326369280
      },
      "steps": {
        "num_steps": 2,
        "k": 2,
        "m": 6,
        "t": [
          1.0,
          0.75,
          0.0
        ],
        "grid_indices": [
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          6,
          12
        ],
        "teacher_grid": "t = linspace(1, 0, 13) warped by t' = 3t / (1 + 2t); grid_indices index this grid",
        "update": "euler",
        "guidance_strength": 1.0
      },
      "fold": "bf16",
      "dtype": "float32",
      "source_checkpoint_sha256": "4d8c96e111239c08670fe7cf88391ac024e2aa70b952e9f3714149c36ccb970f",
      "training_updates": 3000
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  }
}