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Layasaran
/
text_embed_0.5b

Sentence Similarity
sentence-transformers
Safetensors
English
bidirectional_pplx_qwen3
feature-extraction
RAG
domain-adapted
custom-embeddings
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Layasaran/text_embed_0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Layasaran/text_embed_0.5b with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Layasaran/text_embed_0.5b", trust_remote_code=True)
    
    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
text_embed_0.5b
2.4 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Layasaran's picture
Layasaran
Update README.md
1f752f3 verified 5 days ago
  • 1_Pooling
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  • 2_FlexibleQuantizer
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  • .gitattributes
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  • README.md
    2.83 kB
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  • config.json
    1.61 kB
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  • config_sentence_transformers.json
    284 Bytes
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  • configuration.py
    152 Bytes
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  • model.safetensors
    2.38 GB
    xet
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  • modeling.py
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  • modules.json
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  • sentence_bert_config.json
    241 Bytes
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  • st_quantize.py
    4.35 kB
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
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