Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-33 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-33 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-33")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-33") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-33") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0eaa69f54063feafaa7c075dd91806bbe9dafbad19333a6cf791f9b9b2d5f341
- Size of remote file:
- 438 MB
- SHA256:
- 29c4e45bcd51b9ba3716d21f16caae4c258b93cf9e0a54d4247588643e9af15b
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