Instructions to use Jeevesh8/bert_ft_cola-56 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-56 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-56")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-56") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-56") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcc41a7a8d99a5813446f462a171809779c527984eaa066a08a54686cd9c3535
- Size of remote file:
- 438 MB
- SHA256:
- 982b3eec8d4e1b6280268cdabd035d30e08e87ca291cc856328800e5bc78b48d
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