Deploy HuggingFace pretained model (multiple bin files) to AWS Sagemaker

It’s my understanding that you’ll need to merge them into a single pytorch_model.bin I don’t recall my original source, but I had this saved in my notes, so please make any necessary changes for your project.

• Create a new directory and copy all the bin files of your model into it.
• Install the torch library if you haven't already done so. pip install torch
• Use the following Python code to merge the bin files into one:

import torch

bin_files_path = "path/to/your/bin/files/directory"
output_path = "path/to/output/merged/bin/file/pytorch_model.bin"

# Create an empty state dictionary
state_dict = {}
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# Load the weights from each bin file and merge them into the state dictionary
for bin_file in sorted(os.listdir(bin_files_path)):
    if bin_file.endswith(".bin"):
        model_state_dict = torch.load(os.path.join(bin_files_path, bin_file), map_location=device)
        state_dict.update(model_state_dict)

# Save the merged state dictionary as a single bin file
torch.save(state_dict, output_path)

After merging the bin files into one, you should be able to deploy your model into SageMaker using the merged pytorch_model.bin file.