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sayby
/
prot_albert_pfam

Text Classification
Transformers
Safetensors
albert
feature-extraction
biology
Protein
Pfam family
classification
custom_code
Model card Files Files and versions
xet
Community

Instructions to use sayby/prot_albert_pfam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sayby/prot_albert_pfam with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="sayby/prot_albert_pfam", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("sayby/prot_albert_pfam", trust_remote_code=True)
    model = AutoModel.from_pretrained("sayby/prot_albert_pfam", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
prot_albert_pfam
896 MB
Ctrl+K
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  • 1 contributor
History: 26 commits
sayby's picture
sayby
Update README.md
b7cd955 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    2.07 kB
    Update README.md almost 2 years ago
  • config.json
    924 Bytes
    Upload model almost 2 years ago
  • model.safetensors
    896 MB
    xet
    Upload model almost 2 years ago
  • prot_albert_model.py
    1.46 kB
    Upload model almost 2 years ago
  • special_tokens_map.json
    286 Bytes
    Upload tokenizer almost 2 years ago
  • spiece.model
    238 kB
    xet
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.27 kB
    Upload tokenizer almost 2 years ago