Sentence Similarity
sentence-transformers
PyTorch
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use BAAI/bge-m3-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-m3-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-m3-unsupervised") 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:
- 80cb9e33e3a05bef8e7c6ec6101750356f89857451278f216f718d13cbf8cbd9
- Size of remote file:
- 2.27 GB
- SHA256:
- 206f59b77411b290d8a5a317863fbcf1de979e4ed5a8181de9c50fa21fea87ef
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