Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/std_0pnt2_bert_ft_cola-72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/std_0pnt2_bert_ft_cola-72")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-72") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-72") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cf9729c51bea3536c664f37771f0717fb506a14c4112344db6a89b237496045
- Size of remote file:
- 438 MB
- SHA256:
- 751c6ab775aaf791105442340b2bcdc9c5d037e71a9fdaa849a5efda42da48a5
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