Instructions to use ayala-usma/first_setfit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ayala-usma/first_setfit_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ayala-usma/first_setfit_model") 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 ayala-usma/first_setfit_model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("ayala-usma/first_setfit_model") 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 ayala-usma/first_setfit_model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ayala-usma/first_setfit_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ayala-usma/first_setfit_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ayala-usma/first_setfit_model/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 4170bb2fe6fa74c4580d31101787b43010a939995b2efdb15f4f1755f577dbac
- Size of remote file:
- 438 MB
- SHA256:
- 990ad68efa6772892dc8e61aefeb76090246b9bd04496b7bbe407f17146368fe
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