Instructions to use Jeevesh8/bert_ft_cola-69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-69")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-69") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-69") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89734ddbe1aeacc4be2e7b2027df5726f2cb5f1d44ca43dc86af537d866f556d
- Size of remote file:
- 438 MB
- SHA256:
- dce638f93075b88d63bb9238c96a9278cf0f818c50e5b5ab0901e64ab27edec2
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