Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-41 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-41 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-41")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-41") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-41") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f555f4a4cf85c7a5cdc640b46979f65deb6fb02cd45856902cf58b66efce24f
- Size of remote file:
- 438 MB
- SHA256:
- 1ee3a574e4236f8109143816e42ba6f38bf0d137d308c1ad1ba82cdb1e4a0425
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