Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-22 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-22 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-22")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-22") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-22") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3181161047e0c2aba89dd705939183a0dc1d5346569e92f34c933a4290b23bae
- Size of remote file:
- 438 MB
- SHA256:
- 192d6e338d10a3470b165a4fe50ab9ef2f674277e8a5eac0d69c232249288f94
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