Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/std_0pnt2_bert_ft_cola-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/std_0pnt2_bert_ft_cola-43")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-43") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-43") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57c3ca73c4f9f71f2d3535d366f009500c2b29a23f322c7cc4b81b681c91c517
- Size of remote file:
- 438 MB
- SHA256:
- e7feb6b4ad7eb85724311ecfba0d4fa1368a60c54dd4a93e8a82cdb0314ed5c9
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