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HIT-TMG
/
KaLM-embedding-multilingual-mini-instruct-v1

Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
4

Instructions to use HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1")
    
    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
KaLM-embedding-multilingual-mini-instruct-v1 / 1_Pooling
296 Bytes
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
YanshekWoo's picture
YanshekWoo
init
d06313e verified over 1 year ago
  • config.json
    296 Bytes
    init over 1 year ago