Instructions to use Jeevesh8/bert_ft_cola-92 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-92 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-92")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-92") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-92") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7eb6647c5c9dcee0c50b1fbc3ea7892611392a86ffb7d92dcfbb40347a64ab78
- Size of remote file:
- 438 MB
- SHA256:
- 072b67069cd9e847a18459be3e3d2a37134291fe7dc96c466fdf41279b63468a
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