Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-74 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-74 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-74")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-74") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-74") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78136254e69b6e2dc893fc440e608c04ad9ed884017a83c280d448fbfbe5324c
- Size of remote file:
- 438 MB
- SHA256:
- b3eee88b86adb2425d288988931e64df4723132e3c097814bf0674f9921a49a9
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