srpone

/

gr-lite

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SRP 43

Hi,

Whats the error when loading?

the model is in .pt format, you can simply use torch.load. See the readme or this example https://github.com/SerendipityOneInc/look-bench/blob/main/examples/01_load_grlite_model.py .

Hey!

The model is being loaded as ordered_dict. So only the state dict in my instance.

# Download the model checkpoint from Hugging Face
model_name = "srpone/gr-lite"
print(f"  Downloading model from {model_name}...")
model_path = hf_hub_download(
    repo_id=model_name,
    filename="gr_lite.pt"
)
# Load the PyTorch model
print(f"  Loading model checkpoint...")
device = "cuda" if torch.cuda.is_available() else "cpu"
model = torch.load(model_path, map_location=device)
        
    # Set to evaluation mode
if hasattr(model, 'eval'):
    model.eval()
print(f"  Model loaded on {device}")
print(f"✅ GR-Lite model loaded from {model_name}")
print(f"   Model type: {type(model)}")
# Check if model has expected methods
if hasattr(model, 'search'):
    print(f"   Model has .search() method for feature extraction")
elif hasattr(model, 'forward') or hasattr(model, '__call__'):
    print(f"   Model has forward/call method")    
# 4. Inspect model structure
print("\n[4/5] Inspecting model structure...")
print(f"Model type: {type(model)}")
# Check available methods
if hasattr(model, '__dict__'):
    print(f"Model attributes: {list(model.__dict__.keys())[:10]}")
# Try to understand the model interface
if hasattr(model, 'search'):
    print("✓ Model has .search() method")
    print("  Usage: model.search(image_paths=images, feature_dim=256)")
elif hasattr(model, 'encode'):
    print("✓ Model has .encode() method")
elif hasattr(model, 'forward'):
    print("✓ Model has .forward() method")
else:
    print("⚠ Model interface unclear - may need custom preprocessing")
print(type(model))
print(model)

  Downloading model from srpone/gr-lite...
  Loading model checkpoint...
  model = torch.load(model_path, map_location=device)
  Model loaded on cpu
✅ GR-Lite model loaded from srpone/gr-lite
   Model type: <class 'collections.OrderedDict'>

[4/5] Inspecting model structure...
Model type: <class 'collections.OrderedDict'>
Model attributes: ['_metadata']
⚠ Model interface unclear - may need custom preprocessing
<class 'collections.OrderedDict'>
OrderedDict([('model.model.embeddings.cls_token', tensor([[[ 0.2212,  0.0030,  0.0093,  ...,  0.0280, -0.0750,  0.0042]]])), ('model.model.embeddings.mask_token', tensor([[[0., 0., 0.,  ..., 0., 0., 0.]]])), ('model.model.embeddings.register_tokens', tensor([[[ 0.0498,  0.0058,  0.0175,  ..., -0.0170,  0.0099, -0.0072],
         [ 0.0565, -0.0025, -0.0033,  ..., -0.0031, -0.0033, -0.0023],
         [ 0.2848,  0.0060, -0.0355,  ...,  0.0010,  0.0213,  0.0027],
         [ 0.1358, -0.0110, -0.0097,  ...,  0.0038, -0.0082,  0.0072]]])), ('model.model.embeddings.patch_embeddings.weight', tensor([[[[ 9.4926e-04, -3.1649e-03,  1.6883e-03,  ...,  3.2896e-04,
            3.6412e-03,  3.7012e-03],
          [-2.3868e-03, -1.2633e-03, -1.3142e-03,  ...,  7.9380e-04,
            8.3349e-05,  7.0990e-04],
          [ 4.2127e-03, -3.7259e-03, -6.9399e-03,  ...,  2.6176e-03,
            2.5157e-03,  2.1281e-03],
          ...,
          [-8.1405e-03, -4.2286e-03, -2.1547e-03,  ...,  1.0677e-02,
            9.4072e-03,  9.1431e-03],
          [-3.7772e-03, -3.2858e-03, -3.9020e-03,  ...,  7.6342e-03,
           -5.4816e-04,  1.1635e-02],
          [-6.9525e-03, -4.6509e-03, -3.3648e-03,  ...,  3.3205e-03,
            5.4904e-03,  8.8724e-03]],
...
        ...,
        [-0.0965, -0.0428,  0.0147,  ...,  0.1149,  0.0543, -0.0878],
        [-0.0235,  0.1640,  0.0035,  ..., -0.0304, -0.0123, -0.0062],
        [-0.0800, -0.1210,  0.0233,  ..., -0.0272,  0.1435,  0.1071]])), ('model.model.layer.23.mlp.down_proj.bias', t