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BAAI
/
BGE-VL-MLLM-S2

Sentence Similarity
sentence-transformers
Safetensors
English
llava_next
multimodal-retrieval
embedding-model
custom_code
Model card Files Files and versions
xet
Community
6

Instructions to use BAAI/BGE-VL-MLLM-S2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use BAAI/BGE-VL-MLLM-S2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("BAAI/BGE-VL-MLLM-S2", 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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

When share your fineturn code?

#4 opened about 1 year ago by
classdemo

Can task instruction be changed? And tokenizer bug? what's the difference between q and c embedding?

#3 opened about 1 year ago by
Labmem009

Expanding inputs for image tokens in LLaVa-NeXT should be done in processing. Please add `patch_size` and `vision_feature_select_strategy` to the model's processing config

1
#2 opened about 1 year ago by
thirdinwinter

可惜没有中文

🔥👍 1
#1 opened about 1 year ago by
limoncc
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