Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-64 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-64 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-64")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-64") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49b9f0820fade43645bb230e7f21da6eb69a8fb244575c17cb69c9144f900bac
- Size of remote file:
- 438 MB
- SHA256:
- b8a98a13052e2536fde256a0df8d24f5785ec8cdc1617214f401bbab87bdb309
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