Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-68 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-68 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-68")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-68") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-68") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14333830f218f855b5f746c4289c0eb15019df02f4bb511e6dbd75e59be9f129
- Size of remote file:
- 438 MB
- SHA256:
- 9c5713daf1522757e05d8f15b9a796b4c20c6ef9d68a7bfbf0cc8a243e328094
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