Instructions to use StanBienaives/question_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StanBienaives/question_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StanBienaives/question_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("StanBienaives/question_classification") model = AutoModelForSequenceClassification.from_pretrained("StanBienaives/question_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff6faa5a4eb8c3915a685b98a5a4cc3197e5f4874b3fc81a6a4c4c5ad917c5cb
- Size of remote file:
- 553 MB
- SHA256:
- ed6f679b672995d9d190fa2284963c59801359b8805eaa1d483ce8c7ba74cdc6
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