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smallsuper
/
falcon-7b-4bit-32rank

Feature Extraction
Transformers
Safetensors
falcon
custom_code
Model card Files Files and versions
xet
Community

Instructions to use smallsuper/falcon-7b-4bit-32rank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use smallsuper/falcon-7b-4bit-32rank with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="smallsuper/falcon-7b-4bit-32rank", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("smallsuper/falcon-7b-4bit-32rank", trust_remote_code=True)
    model = AutoModel.from_pretrained("smallsuper/falcon-7b-4bit-32rank", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
falcon-7b-4bit-32rank
14.1 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
smallsuper's picture
smallsuper
Upload 12 files
070f540 verified about 2 years ago
  • loftq_init
    Upload 12 files about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    607 Bytes
    Create README.md about 2 years ago
  • config.json
    1.3 kB
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  • model-00001-of-00003.safetensors
    4.98 GB
    xet
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  • model-00002-of-00003.safetensors
    4.97 GB
    xet
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  • model-00003-of-00003.safetensors
    3.89 GB
    xet
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  • model.safetensors.index.json
    14.5 kB
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  • special_tokens_map.json
    395 Bytes
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  • tokenizer.json
    2.73 MB
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  • tokenizer_config.json
    2.64 kB
    Upload 12 files about 2 years ago