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:
- c79b3cde48a5e1e523cba383ecb3e377394ffcaa745bb14c1a94561b4adefdaf
- Size of remote file:
- 2.1 MB
- SHA256:
- 19bfbae397c2b7524158c919d0e9b19393c5639d098f0a66932c91ed8f5f9abb
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