Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-19 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-19 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-19")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-19") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-19") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d3b4f1b39e36c5e84790c2651ab26c9becb518a4229b961dda0045388abedd8
- Size of remote file:
- 438 MB
- SHA256:
- a821c01d2281308dedce005f252b63e012463cf0f739b84f49c06a5bb3d83083
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