added loading util for specific layers

[shanjiaz]

We were loading the full verifier model only to get the embeddings, specific layers. This util helps saving memory by loading only the shards we needed and returns a dict of layer name -> layers.

Tested locally:

model_path = "shanjiaz/Meta-Llama-3-8B-Instruct-FP8-BLOCK"
layer_names = ["lm_head.weight", "model.embed_tokens.weight"]
layer = load_model_layers(layer_names, model_path)
for k, v in layer.items():
    print(k, v.shape)
    print(f"sample data: {v.flatten()[:5]}")

model_path = "/home/hzhao/.cache/huggingface/hub/models--shanjiaz--Meta-Llama-3-8B-Instruct-FP8-BLOCK/snapshots/ea6d7c1a6a0874d9db6511ce93da2b777f24376f"
layer_names = ["lm_head.weight", "model.embed_tokens.weight"]
layer = load_model_layers(layer_names, model_path)
for k, v in layer.items():
    print(k, v.shape)
    print(f"sample data: {v.flatten()[:5]}")

2025-10-06 14:02:21.042 | INFO     | __main__:_resolve_file:64 - Loading from local directory:
2025-10-06 14:02:21.043 | INFO     | __main__:_resolve_file:64 - Loading from local directory:
2025-10-06 14:02:21.044 | INFO     | __main__:_resolve_file:64 - Loading from local directory:
lm_head.weight torch.Size([128256, 4096])
sample data: tensor([ 0.0098,  0.0175,  0.0037,  0.0222, -0.0194], dtype=torch.bfloat16)
model.embed_tokens.weight torch.Size([128256, 4096])
sample data: tensor([ 0.0013,  0.0054, -0.0022,  0.0003, -0.0024], dtype=torch.bfloat16)
2025-10-06 14:02:52.385 | INFO     | __main__:_resolve_file:70 - Loading from huggingface directory:
2025-10-06 14:02:52.468 | INFO     | __main__:_resolve_file:70 - Loading from huggingface directory:
2025-10-06 14:02:52.508 | INFO     | __main__:_resolve_file:70 - Loading from huggingface directory:
lm_head.weight torch.Size([128256, 4096])
sample data: tensor([ 0.0098,  0.0175,  0.0037,  0.0222, -0.0194], dtype=torch.bfloat16)
model.embed_tokens.weight torch.Size([128256, 4096])
sample data: tensor([ 0.0013,  0.0054, -0.0022,  0.0003, -0.0024], dtype=torch.bfloat16)

[github-actions]

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Commit: e251fc9