Instructions to use Jeevesh8/bert_ft_cola-53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-53 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-53")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-53") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-53") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64153e185a4bab9fcb874e383cbd6ce2c62b11afe0f5c29350ea10ed6f896759
- Size of remote file:
- 438 MB
- SHA256:
- e2aa98875b6cbb30fe3b7ce0a2d064b36bb3ec87ffac2a5ab61fbcc97bd02a0d
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