Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-47 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-47 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-47")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-47") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-47") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2b57fce186e8e9fb99410b26fde15e4fb2981993523fbcc08935f2e979ad8f6
- Size of remote file:
- 438 MB
- SHA256:
- 11f59898f01f9498be7a54d287f52d38bfe7fccd691935274ceaefcd45a8df62
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