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sidbrahim
/
autotrain-NarrativesAnaloguesFINAL

Sentence Similarity
sentence-transformers
TensorBoard
Safetensors
bert
feature-extraction
Trained with AutoTrain
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use sidbrahim/autotrain-NarrativesAnaloguesFINAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use sidbrahim/autotrain-NarrativesAnaloguesFINAL with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("sidbrahim/autotrain-NarrativesAnaloguesFINAL")
    
    sentences = [
        "search_query: i love autotrain",
        "search_query: huggingface auto train",
        "search_query: hugging face auto train",
        "search_query: i love autotrain"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
autotrain-NarrativesAnaloguesFINAL
364 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
sidbrahim's picture
sidbrahim
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6421f94 verified 3 months ago
  • 1_Pooling
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  • checkpoint-199
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  • runs
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  • .gitattributes
    1.52 kB
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  • README.md
    1.4 kB
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  • config.json
    678 Bytes
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  • config_sentence_transformers.json
    199 Bytes
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  • model.safetensors
    90.9 MB
    LFS
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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
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.46 kB
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  • training_args.bin
    5.62 kB
    LFS
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  • training_params.json
    1.02 kB
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  • vocab.txt
    232 kB
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