Text Classification
setfit
Safetensors
English
mpnet
education
classroom-discourse
edubehaviors
assertion
Eval Results (legacy)
Instructions to use StanfordSCALE/assertion_is_off_topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use StanfordSCALE/assertion_is_off_topic with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("StanfordSCALE/assertion_is_off_topic") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from StanfordSCALE/assertion_is_off_topic: direct link, hf CLI and curl.
- Browser
- Download file 7.01 kB
-
https://huggingface.co/StanfordSCALE/assertion_is_off_topic/resolve/main/model_head.pkl
- Command line
-
hf download hf://StanfordSCALE/assertion_is_off_topic/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/StanfordSCALE/assertion_is_off_topic/resolve/main/model_head.pkl
7.01 kB
- Xet hash:
- c188eabaaf878d64221a2b589ec62f54e7ae94424311a45022f2037a5b91c449
- Size of remote file:
- 7.01 kB
- SHA256:
- 4a2356382f373b98419af86b0a562c7745a7d4a2ee712677bf4f19a927686cb9
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