Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-49 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-49 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-49")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-49") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-49") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8270f1268b36d1e8c773811f6fe4ed751f2aef5da9198f3d4eb304853f3e028c
- Size of remote file:
- 438 MB
- SHA256:
- e060168cf4797110f0d9d24a2288b14b165455f370ef7079402390bc08e827fe
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