Text Classification
setfit
PyTorch
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use pacoreyes/StanceFit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use pacoreyes/StanceFit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("pacoreyes/StanceFit") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use pacoreyes/StanceFit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pacoreyes/StanceFit") 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] - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pacoreyes/StanceFit: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/pacoreyes/StanceFit/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pacoreyes/StanceFit/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pacoreyes/StanceFit/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 2b4af17cdb2dc58e8957958ca9b9e8be453990a02eeeedd93a823102e2e42cca
- Size of remote file:
- 438 MB
- SHA256:
- 3657eec47ffaa6f9d7eb5ddc96b8be0ed4dba49d6a4a54761a240c1ebc95fa19
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