Sentence Similarity
sentence-transformers
PyTorch
ONNX
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use RedHatAI/bge-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RedHatAI/bge-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RedHatAI/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
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- sentence-similarity
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tasks:
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- text-embedding
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provider: BAAI
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name: RedHatAI/bge-m3
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description: Multilingual embedding model, for use with Docling.
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readme: https://huggingface.co/RedHatAI/bge-m3/blob/main/README.md
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- sentence-similarity
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tasks:
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- text-embedding
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provider: BAAI
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name: RedHatAI/bge-m3
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description: Multilingual embedding model, for use with Docling.
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readme: https://huggingface.co/RedHatAI/bge-m3/blob/main/README.md
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