Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-59 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-59 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-59")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-59") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-59") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 008ae5c6b183835d98e326e012b9051899b44c64964826a3d95e51a25d8c5909
- Size of remote file:
- 438 MB
- SHA256:
- 03a38a022bf8b3366b472444bd32ea8c040aaff2e98ee458706492c17776830d
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