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:
- 90fd1a88f448bdba099d4c53e265ef449b914fc5b6847c4768ba0f175ad7bb71
- Size of remote file:
- 137 kB
- SHA256:
- b99d878d102a40bbcb30dce5b6bd54891ecda8f23e2e0d78aab8291183834f86
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