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scrc-dnai
/
Directional_Tokens_plus_Unordered_8M

Fill-Mask
Transformers
Safetensors
ntv3
genomics
dna
diploid
zygosity
phase
nucleotide-transformer
continued-pretraining
custom_code
Model card Files Files and versions
xet
Community

Instructions to use scrc-dnai/Directional_Tokens_plus_Unordered_8M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use scrc-dnai/Directional_Tokens_plus_Unordered_8M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="scrc-dnai/Directional_Tokens_plus_Unordered_8M", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("scrc-dnai/Directional_Tokens_plus_Unordered_8M", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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  • checkpoints
    Upload stage2-final 5 months ago
  • .gitattributes
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    initial commit 5 months ago
  • LICENSE
    1.71 kB
    Rewrite model card; add LICENSE, diploid_encode.py, diploid_tokens.tsv 3 days ago
  • README.md
    16.3 kB
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  • added_tokens.json
    522 Bytes
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  • config.json
    1.68 kB
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  • configuration_ntv3_pretrained.py
    8.09 kB
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  • diploid_encode.py
    9.42 kB
    Rewrite model card; add LICENSE, diploid_encode.py, diploid_tokens.tsv 3 days ago
  • diploid_tokens.tsv
    2.19 kB
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  • model.safetensors
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    xet
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  • modeling_ntv3_pretrained.py
    35.2 kB
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  • tokenization_ntv3.py
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  • tokenizer_config.json
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  • vocab.json
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