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Nanthasit
/
sakthai-embedding-multilingual

Sentence Similarity
sentence-transformers
Safetensors
multilingual
bert
embeddings
feature-extraction
cross-lingual
semantic-search
retrieval
rag
multilingual-embeddings
384-dim
minilm
sakthai
house-of-sak
beer-sakthai
cpu-inference
edge
text-embeddings-inference
Eval Results
Model card Files Files and versions
xet
Community

Instructions to use Nanthasit/sakthai-embedding-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Nanthasit/sakthai-embedding-multilingual with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Nanthasit/sakthai-embedding-multilingual")
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle
sakthai-embedding-multilingual
488 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 115 commits
Nanthasit's picture
Nanthasit
cron: re-eval snapshot for embedding-multilingual (#2, run 28)
0c5a313 verified about 2 hours ago
  • .eval_results
    cron: re-eval snapshot for embedding-multilingual (#2, run 28) about 2 hours ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
    747 Bytes
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  • config_sentence_transformers.json
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  • model.safetensors
    471 MB
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  • modules.json
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
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