Instructions to use Jeevesh8/bert_ft_cola-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-43")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-43") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-43") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cbedabd3e50d680cf553239ae5ce1f5a4f323ebfa2f5494968ae3c757b7d24c
- Size of remote file:
- 438 MB
- SHA256:
- 6eefd823fd9819cb9d7c390d85cb1f53f0ba14dbe196ea63ab9f116e98249af0
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