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HIT-TMG
/
KaLM-embedding-multilingual-mini-instruct-v1.5

Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
10

Instructions to use HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5 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-v1.5 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5")
    
    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]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

type mismatch

pinned
5
#6 opened over 1 year ago by
michaelfeil

convert to GGUF format?

17
#8 opened over 1 year ago by
kalle07

This model literally beats all the other models in the needle in the haystack challenge

👍 3
3
#7 opened over 1 year ago by
LPN64

KaLM-embedding-multilingual-max-v1

4
#5 opened over 1 year ago by
gururaser
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