Instructions to use lilaspourpre/rubert-tiny-comp_question_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilaspourpre/rubert-tiny-comp_question_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lilaspourpre/rubert-tiny-comp_question_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lilaspourpre/rubert-tiny-comp_question_classification") model = AutoModelForSequenceClassification.from_pretrained("lilaspourpre/rubert-tiny-comp_question_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d18804cf255c35c5e51347ebaa1d014fe76f34e65f10488a3d220513d3e50c4e
- Size of remote file:
- 117 MB
- SHA256:
- d566271cd8b5e5a1282edeb40ee926b18cd58f2ef5e6ec102267872e84a15df8
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