Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-5 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-5 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-5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-5") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a07acac683ae459b82b42a83478796b3efe625c8d5d81a5b7864997bc64061d
- Size of remote file:
- 438 MB
- SHA256:
- 0e9d19ecab286b5ec9baafff3c2e1cf8dbfc69e28855e32a2cda5939d4c00044
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