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cointegrated
/
rubert-tiny2-sentence-compression

Token Classification
Transformers
PyTorch
Safetensors
bert
Model card Files Files and versions
xet
Community
1

Instructions to use cointegrated/rubert-tiny2-sentence-compression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use cointegrated/rubert-tiny2-sentence-compression with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="cointegrated/rubert-tiny2-sentence-compression")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny2-sentence-compression")
    model = AutoModelForTokenClassification.from_pretrained("cointegrated/rubert-tiny2-sentence-compression")
  • Notebooks
  • Google Colab
  • Kaggle
rubert-tiny2-sentence-compression
236 MB
Ctrl+K
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  • 2 contributors
History: 5 commits
cointegrated's picture
cointegrated
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
69ea7d2 about 3 years ago
  • .gitattributes
    1.23 kB
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • README.md
    2.81 kB
    Update README.md about 3 years ago
  • config.json
    805 Bytes
    The first commit almost 4 years ago
  • model.safetensors
    116 MB
    xet
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • pytorch_model.bin
    116 MB
    xet
    The first commit almost 4 years ago
  • special_tokens_map.json
    112 Bytes
    The first commit almost 4 years ago
  • tokenizer.json
    2.41 MB
    The first commit almost 4 years ago
  • tokenizer_config.json
    379 Bytes
    The first commit almost 4 years ago
  • vocab.txt
    1.08 MB
    The first commit almost 4 years ago