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callaghanmt
/
scibert_embed

Feature Extraction
Transformers
Safetensors
English
bert
scibert
fine-tuned
scientific-embeddings
multi-document-summarization
scitldr
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use callaghanmt/scibert_embed with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="callaghanmt/scibert_embed")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("callaghanmt/scibert_embed")
    model = AutoModel.from_pretrained("callaghanmt/scibert_embed")
  • Notebooks
  • Google Colab
  • Kaggle
scibert_embed
441 MB
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  • 1 contributor
History: 2 commits
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callaghanmt
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fbd53c3 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    2.98 kB
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  • config.json
    638 Bytes
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  • model.safetensors
    440 MB
    xet
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    717 kB
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  • tokenizer_config.json
    1.27 kB
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  • vocab.txt
    228 kB
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