Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-77 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-77 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-77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-77") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-77") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be895ff33b2051fcf5674f1608f8d75509a0c2e4f9fa48a3d042be4631c4c085
- Size of remote file:
- 438 MB
- SHA256:
- 23cce797ff384202449ef52078707b7a6eca41e17b36c9fa12f7181092a1e7c7
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