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ShuaiAnwo
/
pore-codec-rsqf42c12a-517

Feature Extraction
Transformers
Safetensors
PyTorch
English
pore_codec_rsqf42c12a
nanopore
nanopore-sequencing
signal-processing
neural-codec
residual-fsq
finite-scalar-quantization
vector-quantization
representation-learning
foundation-model
biological-signals
genomics
bioinformatics
custom_code
Model card Files Files and versions
xet
Community

Instructions to use ShuaiAnwo/pore-codec-rsqf42c12a-517 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ShuaiAnwo/pore-codec-rsqf42c12a-517 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ShuaiAnwo/pore-codec-rsqf42c12a-517", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ShuaiAnwo/pore-codec-rsqf42c12a-517", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
pore-codec-rsqf42c12a-517
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  • 1 contributor
History: 4 commits
ShuaiAnwo's picture
ShuaiAnwo
Update README.md
50c04d5 verified about 1 month ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    7.62 kB
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  • config.json
    329 Bytes
    Upload folder using huggingface_hub about 1 month ago
  • model.safetensors
    6.22 MB
    xet
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  • modeling_pore_codec.py
    20.4 kB
    Upload folder using huggingface_hub about 1 month ago
  • pore_feature_extractor.py
    9.16 kB
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  • preprocessor_config.json
    303 Bytes
    Upload folder using huggingface_hub about 1 month ago