Text Classification
sentence-transformers
PyTorch
Safetensors
setfit
mpnet
text-embeddings-inference
Instructions to use vgarg/setfit_zero_shot_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vgarg/setfit_zero_shot_test with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vgarg/setfit_zero_shot_test") 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 vgarg/setfit_zero_shot_test with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("vgarg/setfit_zero_shot_test") 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 vgarg/setfit_zero_shot_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/vgarg/setfit_zero_shot_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vgarg/setfit_zero_shot_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vgarg/setfit_zero_shot_test/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 9981c5f8ad5f4bdde510cca0fb39babfa5b466cf792a80dd6c531726f056b564
- Size of remote file:
- 438 MB
- SHA256:
- 2b904b9c82753f43ae6df5de76cba775d9bd6909f561caa4739308ed16ccb35e
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