Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-15 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-15 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-15")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-15") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-15") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7ded29de15b1d6ae6bb9c9e8581258a73d9961fff4b184814683521e8fe1715
- Size of remote file:
- 438 MB
- SHA256:
- 365b03b8f0570ebb6df3b0ae9e42799c925fa1a74bdaea3e2786710e0049bb71
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