Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-7 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-7 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-7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-7") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 601f9b3cfb81544b8316c00a9e4166498b6bbf742c7a79ed049641fd443af893
- Size of remote file:
- 438 MB
- SHA256:
- d879b8e52df8c268f6c857ba442db2e9972ef90a9ffe9fb610bd75765c93f3d1
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