Instructions to use Jeevesh8/bert_ft_cola-70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-70")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-70") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-70") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f40e595f5fc376d7e98ca0f2b10a1749804bfb3199c01c63706a586a0d01f02d
- Size of remote file:
- 438 MB
- SHA256:
- 54c9db90cd09d90f3077635258d29f4250f8adc7bb85cc5ce6263b502fe59359
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