Instructions to use wentingzhao/question-evaluator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wentingzhao/question-evaluator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wentingzhao/question-evaluator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wentingzhao/question-evaluator") model = AutoModelForSequenceClassification.from_pretrained("wentingzhao/question-evaluator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from wentingzhao/question-evaluator: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/wentingzhao/question-evaluator/resolve/main/tokenizer.model
- Command line
-
hf download hf://wentingzhao/question-evaluator/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/wentingzhao/question-evaluator/resolve/main/tokenizer.model
500 kB
- Xet hash:
- 409b63d0f14ab5da7909ddcb93f85878ef0e4f19bfa91194b68ac5b45a5b6e87
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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