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cuteo23
/
scam_finetuned

Text Classification
sentence-transformers
Safetensors
Transformers
English
mpnet
feature-extraction
sentence-similarity
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use cuteo23/scam_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use cuteo23/scam_finetuned with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("cuteo23/scam_finetuned")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Transformers

    How to use cuteo23/scam_finetuned with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="cuteo23/scam_finetuned")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("cuteo23/scam_finetuned")
    model = AutoModel.from_pretrained("cuteo23/scam_finetuned")
  • Notebooks
  • Google Colab
  • Kaggle
scam_finetuned
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
cuteo23's picture
cuteo23
Update README.md
96a5271 verified 8 months ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
    438 MB
    xet
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  • modules.json
    368 Bytes
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  • sentence_bert_config.json
    60 Bytes
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  • special_tokens_map.json
    1.02 kB
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
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  • vocab.txt
    232 kB
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