Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-31 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-31 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-31")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-31") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-31") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbba10aaffc1248a7a9a3ac74cd68c408bd60cbc7e9717b235d6c490c22cd14e
- Size of remote file:
- 438 MB
- SHA256:
- fd07c4a36a60ab5c2f7e415975d667c8a2b58164de007133648bfd83e0923c36
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