Instructions to use Jeevesh8/bert_ft_cola-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-50")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-50") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db92eaec95ef6cbae615d84f8ca74b4946dd4689fa050d71e4fb3ec407d424ed
- Size of remote file:
- 438 MB
- SHA256:
- 9f21b970eccf36fac9fa3cb4701ae832fec33cca9cb8158ec7e269fbca573d5d
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