Instructions to use Jeevesh8/bert_ft_cola-63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-63 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-63")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-63") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-63") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8dec5f3ba7bba4c94776d9655e1f31d41276b1bb1634dc731963a66940286c7
- Size of remote file:
- 438 MB
- SHA256:
- f8754e62675bc652087c0ec73013475d9742453366b5d409243239b983c08d2b
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