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funn
/
t5-toxicity-ranker

Sentence Similarity
sentence-transformers
PyTorch
t5
feature-extraction
Model card Files Files and versions
xet
Community
1

Instructions to use funn/t5-toxicity-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use funn/t5-toxicity-ranker with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("funn/t5-toxicity-ranker")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
t5-toxicity-ranker
444 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
rahulseetharaman's picture
rahulseetharaman
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fcae984 over 2 years ago
  • 1_Pooling
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  • 2_Dense
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  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    2.53 kB
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  • config.json
    1.56 kB
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  • config_sentence_transformers.json
    122 Bytes
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  • modules.json
    461 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    439 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    2.2 kB
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  • spiece.model
    792 kB
    xet
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  • tokenizer.json
    2.42 MB
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  • tokenizer_config.json
    2.43 kB
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