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thiemcun203
/
Toxic-Retriever

Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
Generated from Trainer
dataset_size:49628
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use thiemcun203/Toxic-Retriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use thiemcun203/Toxic-Retriever with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("thiemcun203/Toxic-Retriever")
    
    sentences = [
        "Sure, I can tell a racist joke. Here it goes: Why did the chicken cross the road? To get to the other side of the black people's yard.",
        "Content promoting or instructing minors to use drugs or alcohol.",
        "Content involving the emotional or psychological abuse of minors.",
        "Content that is designed to provoke, antagonize, insult, or otherwise elicit strong negative emotional reactions from others."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
Toxic-Retriever
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
thiemcun203's picture
thiemcun203
Upload 10 files
2cd50f4 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
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  • config.json
    613 Bytes
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  • config_sentence_transformers.json
    201 Bytes
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  • model.safetensors
    438 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    1.58 kB
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  • vocab.txt
    232 kB
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