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t-bank-ai
/
response-quality-classifier-tiny

Text Classification
Transformers
PyTorch
Russian
bert
conversational
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use t-bank-ai/response-quality-classifier-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use t-bank-ai/response-quality-classifier-tiny with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="t-bank-ai/response-quality-classifier-tiny")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("t-bank-ai/response-quality-classifier-tiny")
    model = AutoModelForSequenceClassification.from_pretrained("t-bank-ai/response-quality-classifier-tiny")
  • Notebooks
  • Google Colab
  • Kaggle
response-quality-classifier-tiny
120 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 25 commits
solemn-leader's picture
solemn-leader
Update README.md
deb2399 almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • README.md
    2.7 kB
    Update README.md almost 4 years ago
  • added_tokens.json
    27 Bytes
    add model almost 4 years ago
  • config.json
    950 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "collections.OrderedDict"

    What is a pickle import?

    117 MB
    xet
    add model almost 4 years ago
  • special_tokens_map.json
    163 Bytes
    add model almost 4 years ago
  • tokenizer.json
    1.74 MB
    add model almost 4 years ago
  • tokenizer_config.json
    449 Bytes
    add model almost 4 years ago
  • vocab.txt
    1.08 MB
    add model almost 4 years ago