Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-52 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-52 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-52")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-52") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-52") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 001a144d420226436207c29e5e73ecb86b22597b033c60f1658bb57f9ef32adb
- Size of remote file:
- 438 MB
- SHA256:
- e4081905999811d9dee57c80c0f1c3e381225c7ccfd595f6125f5c0e2aa5e5b6
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