Instructions to use Jeevesh8/bert_ft_cola-89 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-89 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-89")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-89") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-89") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15b91073c5efc38da91bb24574d799b863ddd0af1b292ee05f45f38c2495eb06
- Size of remote file:
- 438 MB
- SHA256:
- 34a93bb01e23eed6486dc854272bf0603bfb3020e45c0aeaeb457893c690dc21
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