Instructions to use germla/satoken-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use germla/satoken-pt with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("germla/satoken-pt") 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-pt with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("germla/satoken-pt") 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-pt: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/germla/satoken-pt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://germla/satoken-pt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/germla/satoken-pt/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- da24e5a8ba319be0aa94277f2fdb2ab877c8c934a0c5f62f3bc013f7b6e245bf
- Size of remote file:
- 471 MB
- SHA256:
- b8608f2ef531a1f9b8efc6e89c4b4e44d571ab587c8ce26f890ad024a2910c00
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