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vprojectx
/
Lewis-44M-Bert-V3

Feature Extraction
Transformers
Safetensors
English
lewis_44m_bert
electra
replaced-token-detection
bert
encoder
rope
geglu
rmsnorm
pretrained-from-scratch
glue
squad
ner
custom_code
Model card Files Files and versions
xet
Community

Instructions to use vprojectx/Lewis-44M-Bert-V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use vprojectx/Lewis-44M-Bert-V3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="vprojectx/Lewis-44M-Bert-V3", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("vprojectx/Lewis-44M-Bert-V3", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Lewis-44M-Bert-V3
176 MB
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  • 1 contributor
History: 8 commits
vprojectx's picture
vprojectx
Upload folder using huggingface_hub
17404c4 verified 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 6 days ago
  • README.md
    25.6 kB
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  • config.json
    1.14 kB
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  • configuration_Lewis_44M_Bert.py
    1.89 kB
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  • finetune_glue_v2.py
    12.6 kB
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  • model.safetensors
    174 MB
    xet
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  • modeling_Lewis_44M_Bert.py
    12.1 kB
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  • results.json
    829 Bytes
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  • seed_stats.json
    1.34 kB
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  • tokenizer.json
    2.12 MB
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  • tokenizer_config.json
    326 Bytes
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