Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-79 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-79 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-79")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-79") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-79") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 954927a222a5da53a33cbf89f181aed2fc81b42402a46bef35916abb7e4c74c9
- Size of remote file:
- 438 MB
- SHA256:
- 64f499cfb42718b5a18638b85ac6148abdbc417c0a7bd94fe82055a900f88728
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