Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-6 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-6 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-6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-6") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c2adc387b3d43c988ac20229e60447b606b9a4b60469978c82e530ce5f90383
- Size of remote file:
- 438 MB
- SHA256:
- 9721a245c9926ecef0e4405eee54dc839c24daadb4f09cedc02e01de0f995d2d
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