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JunxiongWang
/
BiGS_512

Fill-Mask
Transformers
PyTorch
JAX
English
BiGS
Model card Files Files and versions
xet
Community
1

Instructions to use JunxiongWang/BiGS_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use JunxiongWang/BiGS_512 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="JunxiongWang/BiGS_512")
    # Load model directly
    from transformers import AutoModelForMaskedLM
    model = AutoModelForMaskedLM.from_pretrained("JunxiongWang/BiGS_512", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
BiGS_512
1.39 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
abhishekmamdapure's picture
abhishekmamdapure
updated readme
caa9d4a about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    4.63 kB
    updated readme about 3 years ago
  • config.json
    581 Bytes
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago
  • flax_model.msgpack
    1.39 GB
    xet
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago
  • special_tokens_map.json
    112 Bytes
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago
  • tokenizer.json
    711 kB
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago
  • tokenizer_config.json
    338 Bytes
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago
  • vocab.txt
    232 kB
    Bidirectional Gated State Space Model. 346M parameters, 23 layers, max sentence length 512 about 3 years ago