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insilicomedicine
/
precious3-gpt

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

Instructions to use insilicomedicine/precious3-gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use insilicomedicine/precious3-gpt with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="insilicomedicine/precious3-gpt", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("insilicomedicine/precious3-gpt", trust_remote_code=True)
    model = AutoModel.from_pretrained("insilicomedicine/precious3-gpt", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
precious3-gpt
191 MB
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  • 1 contributor
History: 27 commits
stefan-insilico's picture
stefan-insilico
Update generation-configs/meta2diff.json
198e490 verified about 2 years ago
  • generation-configs
    Update generation-configs/meta2diff.json about 2 years ago
  • mpt_7b
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  • .gitattributes
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  • .gitignore
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  • README.md
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  • all_entities_with_type.csv
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  • config.json
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  • handler.py
    9.19 kB
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  • model.safetensors
    177 MB
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  • special_tokens_map.json
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  • tokenizer.json
    12.3 MB
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  • tokenizer_config.json
    242 Bytes
    Loaded model configuration and mpt-7b code over 2 years ago