Instructions to use amyma21/sincere_question_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amyma21/sincere_question_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amyma21/sincere_question_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amyma21/sincere_question_classification") model = AutoModelForSequenceClassification.from_pretrained("amyma21/sincere_question_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from amyma21/sincere_question_classification: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/amyma21/sincere_question_classification/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://amyma21/sincere_question_classification@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/amyma21/sincere_question_classification/resolve/refs%2Fpr%2F2/pytorch_model.bin
268 MB
- Xet hash:
- da6e617245bcbfb17de42f0303c5f5eb5a53c472c9728b7047223f1c901c6dc9
- Size of remote file:
- 268 MB
- SHA256:
- 12d29b611e1ba049dc5acf18fc0e4427636089c73aba9cc5043d194c1dbdc3ae
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