Sentence Similarity
sentence-transformers
PyTorch
ONNX
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use shoxa-mir/bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shoxa-mir/bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shoxa-mir/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:
- 0a6de4985f106f58b2c51a0190a2f4cea67a63ae83cb71206a0c78546091a111
- Size of remote file:
- 17.1 MB
- SHA256:
- 6710678b12670bc442b99edc952c4d996ae309a7020c1fa0096dd245c2faf790
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