Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-30 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-30 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-30")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-30") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-30") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ca0af078a3a6de4aeaa496ddb1d6e19679e8edfeb2c66a2472a8b0e717c137e
- Size of remote file:
- 438 MB
- SHA256:
- f61c8e71f37178b95a2634e3eefa11251332266207c7385f124c2c826f0c665d
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