Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-69 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-69 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-69")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-69") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-69") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0bd5310221594b1a61c0a05d4202b41f0c7a7854f8c861e8f4688fb66c1c10a
- Size of remote file:
- 438 MB
- SHA256:
- 05519913847e7aa4f977001583827b472e506102bae3c33a0a286b66f280ecd6
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