Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
agent-skill-retrieval
text-embeddings-inference
Instructions to use tencent/R3-embedding-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tencent/R3-embedding-0.6b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tencent/R3-embedding-0.6b") 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:
- 02c828d27600f7d8b76081d58354eae5da5afefd9a94cc163540f4c830dff949
- Size of remote file:
- 11.4 MB
- SHA256:
- 01632aafb054a5af80c681ecc92d5ef95eb4d90ea11247aef192068b88552ab5
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