Instructions to use Jeevesh8/bert_ft_cola-67 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-67 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-67")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-67") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-67") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0c54741ac3d58744ea6c5a4e0bac15a1d9f5291032fd15c48776ed6b536f337
- Size of remote file:
- 438 MB
- SHA256:
- 231f9947ec3c874d4fda4f91f3f415b2d5d7f19e33b401bbd82a13df7bf871d1
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