Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-16 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-16 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-16")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-16") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae0857051dbf42076632dd66065c558d0bc5700ab3d0735f88db90dcac99aad9
- Size of remote file:
- 438 MB
- SHA256:
- 558c5abdfde6794ed3c6872eca7efb01fdfe0535747f37618f5da6831b7ef323
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