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https://github.com/ggml-org/llama.cpp.git
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5a6bc6b1a6
* model-conversion: add model card template for embeddings [no ci] This commit adds a separate model card template (model repository README.md template) for embedding models. The motivation for this is that there server command for the embedding model is a little different and some addition information can be useful in the model card for embedding models which might not be directly relevant for causal models. * squash! model-conversion: add model card template for embeddings [no ci] Fix pyright lint error. * remove --pooling override and clarify embd_normalize usage
79 lines
2.6 KiB
Python
Executable File
79 lines
2.6 KiB
Python
Executable File
#!/usr/bin/env python3
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from huggingface_hub import HfApi
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import argparse
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# This script requires that the environment variable HF_TOKEN is set with your
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# Hugging Face API token.
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api = HfApi()
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def load_template_and_substitute(template_path, **kwargs):
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try:
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with open(template_path, 'r', encoding='utf-8') as f:
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template_content = f.read()
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return template_content.format(**kwargs)
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except FileNotFoundError:
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print(f"Template file '{template_path}' not found!")
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return None
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except KeyError as e:
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print(f"Missing template variable: {e}")
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return None
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parser = argparse.ArgumentParser(description='Create a new Hugging Face model repository')
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parser.add_argument('--model-name', '-m', help='Name for the model', required=True)
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parser.add_argument('--namespace', '-ns', help='Namespace to add the model to', required=True)
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parser.add_argument('--org-base-model', '-b', help='Original Base model name', default="")
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parser.add_argument('--no-card', action='store_true', help='Skip creating model card')
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parser.add_argument('--private', '-p', action='store_true', help='Create private model')
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parser.add_argument('--embedding', '-e', action='store_true', help='Use embedding model card template')
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parser.add_argument('--dry-run', '-d', action='store_true', help='Print repository info and template without creating repository')
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args = parser.parse_args()
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repo_id = f"{args.namespace}/{args.model_name}-GGUF"
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print("Repository ID: ", repo_id)
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repo_url = None
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if not args.dry_run:
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repo_url = api.create_repo(
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repo_id=repo_id,
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repo_type="model",
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private=args.private,
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exist_ok=False
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)
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if not args.no_card:
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if args.embedding:
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template_path = "scripts/embedding/modelcard.template"
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else:
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template_path = "scripts/causal/modelcard.template"
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print("Template path: ", template_path)
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model_card_content = load_template_and_substitute(
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template_path,
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model_name=args.model_name,
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namespace=args.namespace,
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base_model=args.org_base_model,
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)
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if args.dry_run:
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print("\nTemplate Content:\n")
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print(model_card_content)
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else:
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if model_card_content:
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api.upload_file(
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path_or_fileobj=model_card_content.encode('utf-8'),
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path_in_repo="README.md",
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repo_id=repo_id
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)
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print("Model card created successfully.")
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else:
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print("Failed to create model card.")
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if not args.dry_run and repo_url:
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print(f"Repository created: {repo_url}")
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