Instructions to use cl-nagoya/ruri-pt-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cl-nagoya/ruri-pt-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cl-nagoya/ruri-pt-base") 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 cl-nagoya/ruri-pt-base: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/cl-nagoya/ruri-pt-base/resolve/main/model.safetensors
- Command line
-
hf download hf://cl-nagoya/ruri-pt-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/cl-nagoya/ruri-pt-base/resolve/main/model.safetensors
445 MB
- Xet hash:
- b563190818a24e1ab70c1e4c595a05cd1bd037611b2d2dc45202955c0b6d53c5
- Size of remote file:
- 445 MB
- SHA256:
- 34134d2e748f250a12b865956b595df3cf2b8b4790f3ccdcd5dc8fa23b3c337f
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