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ShwetActhq
/
sbert_actionable

Feature Extraction
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use ShwetActhq/sbert_actionable with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="ShwetActhq/sbert_actionable")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("ShwetActhq/sbert_actionable")
    model = AutoModel.from_pretrained("ShwetActhq/sbert_actionable")
  • Notebooks
  • Google Colab
  • Kaggle
sbert_actionable
70.5 MB
Ctrl+K
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  • 1 contributor
History: 11 commits
ShwetActhq's picture
ShwetActhq
Upload vocab.txt
0963ce3 almost 4 years ago
  • .gitattributes
    1.38 kB
    initial commit almost 4 years ago
  • classifier.pkl
    3.86 kB
    xet
    Upload classifier.pkl almost 4 years ago
  • config.json
    741 Bytes
    Upload config.json almost 4 years ago
  • config_sentence_transformers.json
    122 Bytes
    Upload config_sentence_transformers.json almost 4 years ago
  • modules.json
    229 Bytes
    Upload modules.json almost 4 years ago
  • pytorch_model.bin
    69.6 MB
    xet
    Upload pytorch_model.bin almost 4 years ago
  • sentence_bert_config.json
    53 Bytes
    Upload sentence_bert_config.json almost 4 years ago
  • special_tokens_map.json
    125 Bytes
    Upload special_tokens_map.json almost 4 years ago
  • tokenizer.json
    712 kB
    Upload tokenizer.json almost 4 years ago
  • tokenizer_config.json
    606 Bytes
    Upload tokenizer_config.json almost 4 years ago
  • vocab.txt
    232 kB
    Upload vocab.txt almost 4 years ago