Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-0 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-0 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-0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-0") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8bd18c74530657fa51c21359d6b0b935cf7de5e16a2415882dee3da01891d02
- Size of remote file:
- 438 MB
- SHA256:
- 97ff1d0d7f56f9507953ee170fd64092e3136cd22f51f485ae3f201783f56664
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