Instructions to use germla/satoken-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use germla/satoken-ru with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("germla/satoken-ru") 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] - setfit
How to use germla/satoken-ru with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("germla/satoken-ru") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from germla/satoken-ru: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/germla/satoken-ru/resolve/main/tokenizer.json
- Command line
-
hf download hf://germla/satoken-ru/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/germla/satoken-ru/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- fe584e09808b408472e9556eb0d8db4b797690702ab6f43ad18e59f5b5b2cd10
- Size of remote file:
- 17.1 MB
- SHA256:
- b60b6b43406a48bf3638526314f3d232d97058bc93472ff2de930d43686fa441
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