Instructions to use Jeevesh8/bert_ft_cola-58 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-58 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-58")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-58") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-58") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86defd7aa2d0f7ed0704938e95cef8d1c9c234f9174cb5bbc2357a59f2d99048
- Size of remote file:
- 438 MB
- SHA256:
- 2ec1876cdd26b3fd8055d4ce605c4c82dc52d6aa53fa2e1c2c047fc837e885b2
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