Compare two models in huggingface format

compare.py

from transformers import AutoModel
import torch

# Load the models
model1 = AutoModel.from_pretrained('bigcode/starcoderbase')  # replace with your model names
model2 = AutoModel.from_pretrained('bigcode/starcoder')

# Retrieve the state dictionaries
state_dict1 = model1.state_dict()
state_dict2 = model2.state_dict()

# For each parameter in the state dictionaries
for param1, param2 in zip(state_dict1.items(), state_dict2.items()):
    # Unpack the parameter names and tensors
    name1, tensor1 = param1
    name2, tensor2 = param2

    # Check the names are the same (they should be, if the models are of the same architecture)
    if name1 == name2:
        try:
            # Calculate the difference between the two tensors
            difference = torch.nn.functional.mse_loss(tensor1, tensor2)
            
            print(f"Difference in {name1}: {difference}")
        except:
            print(f"Cannot compare {name1} and {name2}")
    else:
        print(f"Parameter names do not match: {name1}, {name2}")