Instructions to use Jeevesh8/bert_ft_cola-96 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-96 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-96")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-96") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-96") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1c652385267169dcd8d0135fa59a59a67ba8cab865d71c0f1f75c5d514ca09c
- Size of remote file:
- 438 MB
- SHA256:
- 4f0b0f7c9cc95b2f10fbc42cd3ac190bf5bb702714da8a0a8f25c54a32e811b2
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