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aisingapore
/
sealion-bert-large

Fill-Mask
Transformers
Safetensors
bert
custom_code
Model card Files Files and versions
xet
Community

Instructions to use aisingapore/sealion-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use aisingapore/sealion-bert-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="aisingapore/sealion-bert-large", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("aisingapore/sealion-bert-large", trust_remote_code=True)
    model = AutoModelForMaskedLM.from_pretrained("aisingapore/sealion-bert-large", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
sealion-bert-large
2.67 GB
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  • 1 contributor
History: 2 commits
ngannt's picture
ngannt
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  • .gitattributes
    1.52 kB
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  • README.md
    3.88 kB
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  • bert_layers.py
    47.4 kB
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  • bert_padding.py
    6.29 kB
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  • config.json
    813 Bytes
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  • configuration_bert.py
    1.02 kB
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  • flash_attn_triton.py
    42.8 kB
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  • model.safetensors
    2.67 GB
    xet
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  • special_tokens_map.json
    135 Bytes
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  • tokenization_SEA_BPE.py
    11.7 kB
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  • tokenizer.model
    4.84 MB
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  • tokenizer_config.json
    453 Bytes
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