Instructions to use TencentBAC/Conan-embedding-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TencentBAC/Conan-embedding-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TencentBAC/Conan-embedding-v1") 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] - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from TencentBAC/Conan-embedding-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.3 GB
-
https://huggingface.co/TencentBAC/Conan-embedding-v1/resolve/main/model.safetensors
- Command line
-
hf download hf://TencentBAC/Conan-embedding-v1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/TencentBAC/Conan-embedding-v1/resolve/main/model.safetensors
1.3 GB
- Xet hash:
- d91a5593073f4b7d806ab81083c430cf8df01b89a7603bfd2990e59d05738a37
- Size of remote file:
- 1.3 GB
- SHA256:
- af3bb73a4158ae8c4872740ec2a547363b0cc49075a64a15dfac1048af0b5cf2
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