Instructions to use Jeevesh8/bert_ft_cola-68 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-68 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-68")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-68") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-68") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 709d7b960d5cab5a76006bac280f2f16a3ff5c6ba23fd3b7296111502ee21288
- Size of remote file:
- 438 MB
- SHA256:
- 4409b70cb71ced3f8cedb8a60e7e24feaedf81f80de57a3c0d2c3a67df3d6a01
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