Instructions to use Jeevesh8/bert_ft_cola-93 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-93 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-93")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-93") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-93") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78514d185973b798cc8222e825ee43841e6126c40490a66e8ba7637dda9883f9
- Size of remote file:
- 438 MB
- SHA256:
- 0b7cca5ee0e43af2324b18297797db50a25b81b185c3cc2acdc4171c003ee0a8
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