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FreakingPotato
/
NucEL

Feature Extraction
Transformers
PyTorch
Safetensors
English
modernbert
genomics
nucleotide
dna
sequence-modeling
biology
bioinformatics
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use FreakingPotato/NucEL with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="FreakingPotato/NucEL")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("FreakingPotato/NucEL")
    model = AutoModel.from_pretrained("FreakingPotato/NucEL")
  • Notebooks
  • Google Colab
  • Kaggle
NucEL
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  • 1 contributor
History: 9 commits
FreakingPotato's picture
FreakingPotato
Upload tokenizer_config.json with huggingface_hub
723b30c verified 5 months ago
  • .gitattributes
    1.52 kB
    initial commit 9 months ago
  • README.md
    2.09 kB
    Upload README.md with huggingface_hub 5 months ago
  • config.json
    1.36 kB
    Upload config.json with huggingface_hub 5 months ago
  • model.safetensors
    369 MB
    xet
    Upload NucEL model with comprehensive documentation 9 months ago
  • model_index.json
    296 Bytes
    Upload NucEL model with comprehensive documentation 9 months ago
  • pytorch_model.bin
    369 MB
    xet
    Upload NucEL model with comprehensive documentation 9 months ago
  • special_tokens_map.json
    173 Bytes
    Upload NucEL model with comprehensive documentation 9 months ago
  • tokenizer.py
    7.97 kB
    Upload tokenizer.py with huggingface_hub 5 months ago
  • tokenizer_config.json
    1.48 kB
    Upload tokenizer_config.json with huggingface_hub 5 months ago
  • vocab.json
    503 Bytes
    Upload NucEL model with comprehensive documentation 9 months ago