Instructions to use Jeevesh8/bert_ft_cola-30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-30")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-30") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-30") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f237a5be2550debd50f1a44957ef4184ea3af1f0d0f91a2bd370e5f56ea33732
- Size of remote file:
- 438 MB
- SHA256:
- 5eac7a98bac70811ca0567dcbd9aaefc6a3d9e9bd18a7132ab1b9747b36f4f8c
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