Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-40 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-40 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-40")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-40") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-40") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1935168028e87e173084bc70d3992fe1c43847cfef4c699defe77871b40317a5
- Size of remote file:
- 438 MB
- SHA256:
- a43d649346c15f382c29bae3813606b40807d9f749f15a610df6f7de8ff32f1f
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