Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-71 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-71 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-71")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-71") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-71") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 097fae808d165df29a9a7d6c62f5eb210d1b6a3e54d3d91b83dcf3221323ff3e
- Size of remote file:
- 438 MB
- SHA256:
- 5680a94f4fc5d2f769c71a85cbd5167961fe6bde44a5b8470b7552631cc3e757
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