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* examples : add model conversion tool/example This commit adds an "example/tool" that is intended to help in the process of converting models to GGUF. Currently it supports normal causal models and embedding models. The readme contains instructions and command to guide through the process. The motivation for this to have a structured and repeatable process for model conversions and hopefully with time improve upon it to make the process easier and more reliable. We have started to use this for new model conversions internally and will continue doing so and improve it as we go along. Perhaps with time this should be placed in a different directory than the examples directory, but for now it seems like a good place to keep it while we are still developing it. * squash! examples : add model conversion tool/example Remove dependency on scikit-learn in model conversion example. * squash! examples : add model conversion tool/example Update transformer dep to use non-dev version. And also import `AutoModelForCausalLM` instead of `AutoModel` to ensure compatibility with the latest version. * squash! examples : add model conversion tool/example Remove the logits requirements file from the all requirements file.
63 lines
2 KiB
Python
Executable file
63 lines
2 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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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 = 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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template_path = "scripts/readme.md.template"
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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 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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print(f"Repository created: {repo_url}")
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