Spaces:
Sleeping
Sleeping
| """Create the private Docker Space and upload this deployment source tree.""" | |
| import argparse | |
| from pathlib import Path | |
| from huggingface_hub import HfApi, Volume | |
| def main(): | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--repo", default="Angshul/Tensor-Pruning-API") | |
| parser.add_argument("--model-repo", help="Optionally mount a model repo read-only at /models") | |
| args = parser.parse_args() | |
| api = HfApi() | |
| options = {} | |
| if args.model_repo: | |
| options["space_volumes"] = [ | |
| Volume(type="model", source=args.model_repo, mount_path="/models", read_only=True) | |
| ] | |
| api.create_repo(args.repo, repo_type="space", space_sdk="docker", private=True, **options) | |
| api.upload_folder(repo_id=args.repo, repo_type="space", folder_path=Path(__file__).parent, | |
| allow_patterns=["README.md", "Dockerfile", "space_app.py", | |
| "pyproject.toml", "tensor_pruning/*.py", | |
| "tensor_pruning/kernel.cpp"], | |
| commit_message="Deploy the CPU tensor-pruning API") | |
| print(f"https://huggingface.co/spaces/{args.repo}") | |
| if __name__ == "__main__": | |
| main() | |