Instructions to use nomic-ai/CodeRankEmbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nomic-ai/CodeRankEmbed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nomic-ai/CodeRankEmbed", trust_remote_code=True) 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
- Xet hash:
- 2c08597aed3bb850ee42d4c9f38cbfb646762fada0bb8e45d2084f445b43c947
- Size of remote file:
- 547 MB
- SHA256:
- 827529bcd58aef0d9082e66eeff7e7d53a02f62bd005f841a26b3d3e2fb17ebe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.