Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-65 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-65 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-65")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-65") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-65") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35ebb66670b2723a0dc10fb6f5a03e6eabe8fe998b272069dfdc8a5377ca9b33
- Size of remote file:
- 438 MB
- SHA256:
- f6635ce47f8a574074a98a0686277031c23eedfda0a2c8c15d1b91384c128934
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