Instructions to use Jeevesh8/bert_ft_cola-87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-87 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-87")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-87") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-87") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4027fd15d1c6efecb1947c26fa808209419fa8c9a1946c455f0f88202705a1b
- Size of remote file:
- 438 MB
- SHA256:
- 2a87e91251cedbb9520732e3256e929e8fc2bd409390f7d7689c0b7b85b3c79b
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