Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-45 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-45 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-45")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-45") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-45") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fbc41f4c7a622d747b413f42615fa63e28487f2a5dcea93e61e2d904e0427c2
- Size of remote file:
- 438 MB
- SHA256:
- 4f024ed36e56eea280688eecd086ddb3b4b61b659fca8b0ff7b798bd107d7700
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