Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-29 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-29 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-29")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-29") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-29") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f35bd5ac93ce42abc1febf575a8ff19b4643f4ce3441a27f11f7d40f7195d6f1
- Size of remote file:
- 438 MB
- SHA256:
- a18af7bc72a939e001af5f09c4ee01386d3b60a49d88c1046e775d097b900002
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