Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-53 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-53 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-53")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-53") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-53") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89041386c91f53d6cd3e61df33c2bdc033522a7ffdbb1990f7006410fc9a246d
- Size of remote file:
- 438 MB
- SHA256:
- 6811b6b9ea55b8e833ac48d0d14e865a07d808d8467acca6a5bce2f8321a8c97
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