Instructions to use Jeevesh8/bert_ft_cola-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-32")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-32") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3823856d6eba2c18acfeeb807904dee8887140d095e1b94154f79b721b6eee82
- Size of remote file:
- 438 MB
- SHA256:
- 6f941269b4561c42cb48ca0e359f3ed4b32eb130641400fa444507fbc5362c08
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