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HIT-TMG
/
JevEmbed-KaLM-Embedding-V2.5

Feature Extraction
sentence-transformers
Safetensors
qwen2
jevembed
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use HIT-TMG/JevEmbed-KaLM-Embedding-V2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use HIT-TMG/JevEmbed-KaLM-Embedding-V2.5 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("HIT-TMG/JevEmbed-KaLM-Embedding-V2.5", trust_remote_code=True)
    
    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
JevEmbed-KaLM-Embedding-V2.5
2.02 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Yuki131's picture
Yuki131
Update README.md
f23f178 verified about 1 month ago
  • 1_Pooling
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  • assets
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  • lora
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  • .gitattributes
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  • MERGE_MANIFEST.json
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  • README.md
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  • added_tokens.json
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  • config.json
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  • config_sentence_transformers.json
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  • jevembed.yaml
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  • merges.txt
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  • model.safetensors
    1.98 GB
    xet
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  • modeling.py
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  • modules.json
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  • sentence_bert_config.json
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  • special_tokens_map.json
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
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  • vocab.json
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