Instructions to use Jeevesh8/bert-base-uncased_cola_ft_43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert-base-uncased_cola_ft_43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert-base-uncased_cola_ft_43")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert-base-uncased_cola_ft_43") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert-base-uncased_cola_ft_43") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 950e53e7eb9dd6b49f3eec65d041947353143ee43309700817231267207921eb
- Size of remote file:
- 438 MB
- SHA256:
- 57c2ddd32da7f6d1f26033d1b43d7906ff1610a1ff0a70652b1a9d9d8a45444f
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