Instructions to use Jeevesh8/bert_ft_cola-20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-20")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-20") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-20") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe525886c2a87623c92e1c21501e3b7ec81485320fbd683a71ef63a6752a802d
- Size of remote file:
- 438 MB
- SHA256:
- 8fc094a71bf85e05d3d2687eb8702237918df5752677e5ece3cf778310006c2e
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