Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-23 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-23 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-23")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-23") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-23") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d040e18d4efe851d32b79553919c8b0147325d1109c0735d24907fc5a2ef194
- Size of remote file:
- 438 MB
- SHA256:
- 356dcb5fc7eeebd1cf37218b6cfec84bb2ff3c33de33a251d27c7e51b288765e
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