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gziz
/
snippet-extraction

Feature Extraction
Transformers
English
context-compression
rag
extractive-summarization
token-classification
Model card Files Files and versions
xet
Community

Instructions to use gziz/snippet-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use gziz/snippet-extraction with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="gziz/snippet-extraction")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("gziz/snippet-extraction", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
snippet-extraction
600 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
gziz's picture
gziz
Remove generated Python bytecode
30aaaca verified 7 days ago
  • .gitattributes
    1.52 kB
    initial commit 7 days ago
  • README.md
    2.87 kB
    Upload run9 query-aware snippet extractor 7 days ago
  • load_model.py
    1.32 kB
    Upload run9 query-aware snippet extractor 7 days ago
  • model.pt
    596 MB
    xet
    Upload run9 query-aware snippet extractor 7 days ago
  • tokenizer.json
    3.58 MB
    Upload run9 query-aware snippet extractor 7 days ago
  • tokenizer_config.json
    380 Bytes
    Upload run9 query-aware snippet extractor 7 days ago