Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-27 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-27 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-27")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-27") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-27") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1eb27cdc3f5cc53818cf178f69c752a8ea1a3af7373e4d27b4a19d207f742f9b
- Size of remote file:
- 438 MB
- SHA256:
- 904aac509b6efde9b3c203e370e62ef28223601096bf03ea8225f49c4a8d598b
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