Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-61 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-61 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-61")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-61") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-61") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f82292fb1a28cd56fcac10397ce735e1c6c1e70158da347e946fb4a47134395f
- Size of remote file:
- 438 MB
- SHA256:
- 205f2414144256c50c5ff4395218d0c940641cecedc9a1d8b0044b6da2b0d166
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