Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-13 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-13 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-13")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-13") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4348e39c90a88216029e1dce5d9f2e53fa8151c2cd3362255c559fbf2db2865c
- Size of remote file:
- 438 MB
- SHA256:
- ddbcbaa0e109ee19028f6494ed1cd6e2e2f448e8cdb56452c0fedc59bfd52a17
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