Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-78 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-78 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-78")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-78") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-78") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14104949d2cf2565ab29218ba5d54c5bb5bb21f39d8b2689674fec3e1995e57c
- Size of remote file:
- 438 MB
- SHA256:
- e0be9658af5404ef19e0cf59e4041ea55f16d2bc32f4f91a41b18c0a1f5dc483
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