Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

L-NLProc
/
PredEx_InCaseLaw_Pred

Feature Extraction
Transformers
Safetensors
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use L-NLProc/PredEx_InCaseLaw_Pred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use L-NLProc/PredEx_InCaseLaw_Pred with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="L-NLProc/PredEx_InCaseLaw_Pred")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("L-NLProc/PredEx_InCaseLaw_Pred")
    model = AutoModel.from_pretrained("L-NLProc/PredEx_InCaseLaw_Pred")
  • Notebooks
  • Google Colab
  • Kaggle
PredEx_InCaseLaw_Pred
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
ShubhamKumarNigam's picture
ShubhamKumarNigam
Upload tokenizer
1a80347 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    31 Bytes
    initial commit almost 2 years ago
  • config.json
    903 Bytes
    Upload model almost 2 years ago
  • model.safetensors
    438 MB
    xet
    Upload model almost 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer almost 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.27 kB
    Upload tokenizer almost 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer almost 2 years ago