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shmelev
/
genatator-pipeline

Feature Extraction
Transformers
genatator_pipeline
genomics
gene-annotation
dna-language-models
biology
ab-initio
custom_code
Model card Files Files and versions
xet
Community

Instructions to use shmelev/genatator-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use shmelev/genatator-pipeline with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="shmelev/genatator-pipeline", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("shmelev/genatator-pipeline", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
genatator-pipeline / docker
7.22 kB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
gettheworkdone
Set Docker pipeline dtype to float32
98234a1 about 2 months ago
  • Dockerfile
    302 Bytes
    Fix Docker startup and return fasta/faidx/gff/archive outputs about 2 months ago
  • app.py
    2.66 kB
    Set Docker pipeline dtype to float32 about 2 months ago
  • conda-core.yml
    1.49 kB
    Install full pinned core stack and fix CUDA nvcc path in Docker startup about 2 months ago
  • requirements.txt
    762 Bytes
    Fix Docker startup and return fasta/faidx/gff/archive outputs about 2 months ago
  • startup.sh
    2.01 kB
    Fix Docker startup and return fasta/faidx/gff/archive outputs about 2 months ago