Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-38 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-38 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-38")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-38") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-38") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9790cbdcd2b6b55d3def9f404806a28c2235c28e04d3d259e9eca5fb2d115d99
- Size of remote file:
- 438 MB
- SHA256:
- 419eeef459778dfafd4bc3a142e6ae9070d43adc1f85b788bcc50c13cf5e04fc
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