Sentence Similarity
sentence-transformers
Safetensors
English
clip
multimodal-retrieval
embedding-model
custom_code
Instructions to use BAAI/BGE-VL-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/BGE-VL-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/BGE-VL-base", 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
Update README.md
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README.md
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print(scores)
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```
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See the [demo](./retrieval_demo.ipynb) for a complete example of using BGE-VL for multimodel retrieval.
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### 2. BGE-VL-MLLM Models
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print(scores)
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```
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See the [demo](https://github.com/VectorSpaceLab/MegaPairs/blob/main/retrieval_demo.ipynb) for a complete example of using BGE-VL for multimodel retrieval.
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### 2. BGE-VL-MLLM Models
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