Text Classification
setfit
Safetensors
English
mpnet
education
classroom-discourse
edubehaviors
assertion
Eval Results (legacy)
Instructions to use StanfordSCALE/assertion_repeats_a_problem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use StanfordSCALE/assertion_repeats_a_problem with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("StanfordSCALE/assertion_repeats_a_problem") 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_repeats_a_problem: direct link, hf CLI and curl.
- Browser
- Download file 7.01 kB
-
https://huggingface.co/StanfordSCALE/assertion_repeats_a_problem/resolve/main/model_head.pkl
- Command line
-
hf download hf://StanfordSCALE/assertion_repeats_a_problem/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/StanfordSCALE/assertion_repeats_a_problem/resolve/main/model_head.pkl
7.01 kB
- Xet hash:
- 929a847280a36f09fa6c1b5c4881695354fa8a5357472cada46b4852cff01c98
- Size of remote file:
- 7.01 kB
- SHA256:
- 3eac74156da87cd076cce3771649f0754e7da5a916574dcc0c8e6f8901a703a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.