Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-20 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-20 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-20")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-20") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-20") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95e121fd996c1d127b862ac9424f4afc3785985bfab3a05a71c27e84f6ebc729
- Size of remote file:
- 438 MB
- SHA256:
- 76fbb013cc6609f57be5bdd3cf4f51790be06ad77a6310eccca50fcdc0b12378
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