Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-18 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-18 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-18")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-18") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-18") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5634d30e265620b4db9dbc59730b8f5d95dec3e5f76345b62a6a93ed48ecf50c
- Size of remote file:
- 438 MB
- SHA256:
- 73ca361d0298dbec19df519ca8f6793d85c5b337346342c20aa7250f5b4f601d
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