Instructions to use Jeevesh8/bert_ft_cola-85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-85 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-85")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-85") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-85") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67ffb97a1f1c725c7d612484fb2819cd471c1c83c20e481b65684d7bfa0259be
- Size of remote file:
- 438 MB
- SHA256:
- 6d2ea50cbb91d689e3309b9def8489816460ac84ffc026e4bd3d9d9f1671fdc2
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