Instructions to use Jeevesh8/std_0pnt2_bert_ft_cola-63 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-63 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-63")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-63") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/std_0pnt2_bert_ft_cola-63") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54ebf7a1f94f1c8628153e9c1dd6c79e4864378f6a39d8e2641dcea8d5f1d6b2
- Size of remote file:
- 438 MB
- SHA256:
- b0787af64525dd8c6112aae184d1265f561ba6fc54baa5c5a25746b436f3b9ba
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