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raghavagps-group
/
anticp3

Text Classification
Transformers
Safetensors
English
esm
protein-classification
bioinformatics
anticancer
esm2
torch
Model card Files Files and versions
xet
Community

Instructions to use raghavagps-group/anticp3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use raghavagps-group/anticp3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="raghavagps-group/anticp3")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("raghavagps-group/anticp3")
    model = AutoModelForSequenceClassification.from_pretrained("raghavagps-group/anticp3")
  • Notebooks
  • Google Colab
  • Kaggle
anticp3
2.61 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 6 commits
AmishaG's picture
AmishaG
Update README.md
77efdcf verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    2.29 kB
    Update README.md about 1 year ago
  • config.json
    833 Bytes
    Added fine-tuned ESM2 Model about 1 year ago
  • model.safetensors
    2.61 GB
    xet
    Added fine-tuned ESM2 Model about 1 year ago
  • special_tokens_map.json
    125 Bytes
    Adding tokenizer files about 1 year ago
  • tokenizer_config.json
    108 Bytes
    Adding tokenizer files about 1 year ago
  • vocab.txt
    93 Bytes
    Adding tokenizer files about 1 year ago