Instructions to use Jeevesh8/bert_ft_cola-79 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-79 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-79")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-79") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-79") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c00c41bbb4698064c85d00ecef329d83edf23ca1815d4b567a0719f0ab9968c2
- Size of remote file:
- 438 MB
- SHA256:
- 098da540657eee6a0dee923bdd3550d9a25cbaf14d189ff2b5ad7d8c9d80c971
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