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bobox
/
synt-dataset-multi-task

Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:989216
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use bobox/synt-dataset-multi-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use bobox/synt-dataset-multi-task with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("bobox/synt-dataset-multi-task")
    
    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

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  • 1_Pooling
    Push multi-task ST model about 23 hours ago
  • .gitattributes
    1.57 kB
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  • README.md
    7.22 kB
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  • config.json
    1.7 kB
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  • config_sentence_transformers.json
    283 Bytes
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  • model.safetensors
    195 MB
    xet
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    25.3 MB
    xet
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  • tokenizer_config.json
    647 Bytes
    Push multi-task ST model about 23 hours ago