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Youssefbou62
/
MNLP_M3_document_encoder

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

Instructions to use Youssefbou62/MNLP_M3_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Youssefbou62/MNLP_M3_document_encoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Youssefbou62/MNLP_M3_document_encoder")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Youssefbou62/MNLP_M3_document_encoder")
    model = AutoModel.from_pretrained("Youssefbou62/MNLP_M3_document_encoder")
  • Notebooks
  • Google Colab
  • Kaggle
MNLP_M3_document_encoder
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  • 1 contributor
History: 3 commits
Youssefbou62's picture
Youssefbou62
Upload tokenizer
2224330 verified 11 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    5.17 kB
    Upload model 11 months ago
  • config.json
    620 Bytes
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  • model.safetensors
    670 MB
    xet
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  • special_tokens_map.json
    695 Bytes
    Upload tokenizer 11 months ago
  • tokenizer.json
    712 kB
    Upload tokenizer 11 months ago
  • tokenizer_config.json
    1.44 kB
    Upload tokenizer 11 months ago
  • vocab.txt
    232 kB
    Upload tokenizer 11 months ago