Instructions to use rsvalerio/starencoder-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rsvalerio/starencoder-coreml with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rsvalerio/starencoder-coreml") 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:
- f1b70aa749f319a3e44ca48a71e1faa440573c9e0b6a95867aa5db21204e1864
- Size of remote file:
- 247 MB
- SHA256:
- f40519223965e708ddabc030655bacdb3a797c72f2b3a7d76c55a56afd3519a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.