Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-42 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-42 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-42")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-42") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57855ac684ad62700a8b64b336afd11a8b040289ee55cc2f0c5d196456812409
- Size of remote file:
- 438 MB
- SHA256:
- 145d14dba24a063606419c28968001ba9bddfc8af04736e3ea6cdf869fe50cac
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