Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-28 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-28 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-28")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-28") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-28") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25626facbb01a1907976935f7ac9ac3b17fefd60bc2fefcd38680b325bcf2fbc
- Size of remote file:
- 438 MB
- SHA256:
- babf2242da6eea79c88fa181489c1296dd9c0c099d71bf7726f7529d5182c7d0
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