Instructions to use Jeevesh8/bert_ft_cola-82 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-82 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-82")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-82") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-82") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a04aa1fb90c93af91931ca494dcbe38cf33010aadd3776443c7f6bba0d29d34
- Size of remote file:
- 438 MB
- SHA256:
- 53f54ba0e28951fcdf7ca97e8a31ade6c8ab09aa2a265f90bd9841d76c5bece5
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