Sentence Similarity
sentence-transformers
Safetensors
English
clip
multimodal-retrieval
embedding-model
custom_code
Instructions to use tomaarsen/BGE-VL-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/BGE-VL-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/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

- Xet hash:
- 4660555432f563ff397fe00f7f8e05277c09a1009188fddaaaa6887ce30f00d6
- Size of remote file:
- 153 kB
- SHA256:
- 42ad0e1200ba5c8767ea752f6358f6b51719674b064666b415b6ab0ea90ae62b
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