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damlab
/
HIV_V3_Coreceptor

Text Classification
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
4

Instructions to use damlab/HIV_V3_Coreceptor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use damlab/HIV_V3_Coreceptor with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="damlab/HIV_V3_Coreceptor")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("damlab/HIV_V3_Coreceptor")
    model = AutoModelForSequenceClassification.from_pretrained("damlab/HIV_V3_Coreceptor")
  • Notebooks
  • Google Colab
  • Kaggle
HIV_V3_Coreceptor
1.68 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 11 commits
librarian-bot's picture
librarian-bot
Librarian Bot: Update dataset YAML metadata for model
48648a4 about 3 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • README.md
    4.35 kB
    Librarian Bot: Update dataset YAML metadata for model about 3 years ago
  • config.json
    762 Bytes
    add model about 4 years ago
  • pytorch_model.bin
    1.68 GB
    xet
    add model about 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer about 4 years ago
  • tokenizer.json
    1.71 kB
    add tokenizer about 4 years ago
  • tokenizer_config.json
    378 Bytes
    add tokenizer about 4 years ago
  • vocab.txt
    81 Bytes
    add tokenizer about 4 years ago