Sentence Similarity
sentence-transformers
PyTorch
ONNX
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use unsloth/bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use unsloth/bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("unsloth/bge-m3") 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:
- cb96d9dfcb34098366affed600aa899fe66d05a2774a2224b579e772efcf9deb
- Size of remote file:
- 158 kB
- SHA256:
- 5385ca9d6af4124932281039e1366d704d10ed81e905526f795f5732352394bb
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