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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.
80 lines
2.4 KiB
Python
Executable file
80 lines
2.4 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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import sys
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def add_model_to_collection(collection_slug, model_id, note=""):
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"""
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Add a model to an existing collection
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Args:
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collection_slug: The slug of the collection (e.g., "username/collection-name-12345")
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model_id: The model repository ID (e.g., "username/model-name")
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note: Optional note about the model
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Returns:
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True if successful, False if failed
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"""
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# Initialize API
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api = HfApi()
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try:
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user_info = api.whoami()
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print(f"✅ Authenticated as: {user_info['name']}")
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# Verify the model exists
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print(f"🔍 Checking if model exists: {model_id}")
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try:
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model_info = api.model_info(model_id)
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except Exception as e:
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print(f"❌ Model not found or not accessible: {model_id}")
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print(f"Error: {e}")
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return False
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print(f"📚 Adding model to collection...")
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api.add_collection_item(
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collection_slug=collection_slug,
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item_id=model_id,
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item_type="model",
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note=note
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)
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print(f"✅ Model added to collection successfully!")
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print(f"🔗 Collection URL: https://huggingface.co/collections/{collection_slug}")
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return True
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except Exception as e:
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print(f"❌ Error adding model to collection: {e}")
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return False
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def main():
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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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parser = argparse.ArgumentParser(description='Add model to a Huggingface Collection')
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parser.add_argument('--collection', '-c', help='The collection slug username/collection-hash', required=True)
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parser.add_argument('--model', '-m', help='The model to add to the Collection', required=True)
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parser.add_argument('--note', '-n', help='An optional note/description', required=False)
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args = parser.parse_args()
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collection = args.collection
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model = args.model
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note = args.note
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success = add_model_to_collection(
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collection_slug=collection,
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model_id=model,
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note=note
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)
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if success:
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print("\n🎉 Model added successfully!")
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else:
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print("\n❌ Failed to add model to collection")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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