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Den4ikAI
/
rubert_base_response_ranker

Text Classification
Transformers
PyTorch
Russian
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
3

Instructions to use Den4ikAI/rubert_base_response_ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Den4ikAI/rubert_base_response_ranker with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Den4ikAI/rubert_base_response_ranker")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Den4ikAI/rubert_base_response_ranker")
    model = AutoModelForSequenceClassification.from_pretrained("Den4ikAI/rubert_base_response_ranker", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
rubert_base_response_ranker
715 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
tomaarsen's picture
tomaarsen HF Staff
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
6c21236 verified over 1 year ago
  • .gitattributes
    1.48 kB
    initial commit almost 4 years ago
  • README.md
    205 Bytes
    Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers` over 1 year ago
  • config.json
    895 Bytes
    Upload 7 files almost 4 years ago
  • pytorch_model.bin
    712 MB
    xet
    Upload 7 files almost 4 years ago
  • special_tokens_map.json
    112 Bytes
    Upload 7 files almost 4 years ago
  • tokenizer.json
    2.2 MB
    Upload 7 files almost 4 years ago
  • tokenizer_config.json
    413 Bytes
    Upload 7 files almost 4 years ago
  • training_args.bin
    2.8 kB
    xet
    Upload 7 files almost 4 years ago
  • vocab.txt
    1.4 MB
    Upload 7 files almost 4 years ago