Instructions to use Jeevesh8/bert_ft_cola-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-10") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6a045f92ff97ee0784acedb0d77e50fdb7ba60dad3ac690aaa32022d5aa9dca
- Size of remote file:
- 438 MB
- SHA256:
- ef42c166d6227ce15a7d442b2dc85ba72f6ccce5b2809480576abe4f572200d7
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