Text Classification
setfit
Safetensors
English
mpnet
education
classroom-discourse
edubehaviors
assertion
Eval Results (legacy)
Instructions to use StanfordSCALE/assertion_references_logistics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use StanfordSCALE/assertion_references_logistics with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("StanfordSCALE/assertion_references_logistics") 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_references_logistics: direct link, hf CLI and curl.
- Browser
- Download file 7.01 kB
-
https://huggingface.co/StanfordSCALE/assertion_references_logistics/resolve/main/model_head.pkl
- Command line
-
hf download hf://StanfordSCALE/assertion_references_logistics/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/StanfordSCALE/assertion_references_logistics/resolve/main/model_head.pkl
7.01 kB
- Xet hash:
- 2e697872d28c20d6d3aa34e0322d623beeeb6f26c12779bdbe7400fd0394e73d
- Size of remote file:
- 7.01 kB
- SHA256:
- 1d348ed82551eca416eac972375a4e043f15084b00fe927fc7eeaf595cd61e1d
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