Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-4 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-4 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-4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbf2080debbf73598d170e40216df37cceeddc351800227b678992a84c16ba74
- Size of remote file:
- 438 MB
- SHA256:
- 80510edf103a73db2269cd505bb0bad8f017dca17942a3d3255815e12513b925
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