Feature Extraction
sentence-transformers
PyTorch
Chinese
English
bert
sentence-similarity
mteb
RAG
Eval Results (legacy)
text-embeddings-inference
Instructions to use DMetaSoul/Dmeta-embedding-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use DMetaSoul/Dmeta-embedding-zh with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DMetaSoul/Dmeta-embedding-zh") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11f84f36994f7bd1bc3e81f216d3be7fb37f8840ec71191f2299e94712e185c5
- Size of remote file:
- 411 MB
- SHA256:
- a6c2ecb71a1c2a94a74037446a8a7e88d1c9e40e8517d795f4ded414dd091b97
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