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62 lines
1.8 KiB
62 lines
1.8 KiB
"""Upload local directory to HuggingFace Hub.
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This script uploads a specified local directory to HuggingFace Hub as a private repository.
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Example:
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python upload_checkpoint.py --local-dir "models/my_model" --repo-id "org/model-name"
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"""
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import argparse
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import os
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from dotenv import load_dotenv
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from huggingface_hub import HfApi
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def parse_args() -> argparse.Namespace:
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"""Parse command line arguments.
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Returns:
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argparse.Namespace: Parsed arguments
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"""
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parser = argparse.ArgumentParser(description="Upload model to HuggingFace Hub")
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parser.add_argument("--local-dir", type=str, required=True, help="Local directory to upload")
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parser.add_argument("--repo-id", type=str, required=True, help="HuggingFace repository ID")
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parser.add_argument("--public", action="store_true", help="Make repository public (default: private)")
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return parser.parse_args()
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def main():
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"""Main function to upload model."""
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args = parse_args()
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load_dotenv(override=True)
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# Configuration
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HF_TOKEN = os.getenv("HF_TOKEN")
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# Files to ignore during upload
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IGNORE_PATTERNS = [
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"*.log", # Log files
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"*.pyc", # Python cache
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".git*", # Git files
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"*.bin", # Binary files
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"*.pt", # PyTorch checkpoints
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"*.ckpt", # Checkpoints
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"events.*", # Tensorboard
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"wandb/*", # Weights & Biases
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"runs/*", # Training runs
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]
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api = HfApi(token=HF_TOKEN)
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api.create_repo(repo_id=args.repo_id, private=not args.public, exist_ok=True, repo_type="model")
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api.upload_folder(
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folder_path=args.local_dir,
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repo_id=args.repo_id,
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repo_type="model",
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# ignore_patterns=IGNORE_PATTERNS
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)
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print(f"✅ Done: {args.local_dir} -> {args.repo_id}")
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if __name__ == "__main__":
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main()
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