Instructions to use germla/satoken-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use germla/satoken-ko with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("germla/satoken-ko") 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-ko with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("germla/satoken-ko") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from germla/satoken-ko: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/germla/satoken-ko/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://germla/satoken-ko/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/germla/satoken-ko/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- 50f172622f8b0dd81f69a4368a84d1ffb643f205859f7bcab25dba2f3160b8c5
- Size of remote file:
- 471 MB
- SHA256:
- cac722c8d0437f12337333bd5ca3d9e6452ef74165a41a2a49cfef30b9c2d328
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