Instructions to use Jeevesh8/bert_ft_cola-73 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-73 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-73")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-73") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-73") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8258a0d3c0098ddd77a71826cfaf4e8b6814388a417962eedb29d093e6b32da2
- Size of remote file:
- 438 MB
- SHA256:
- 516fb5bb8233380d3b4c457f0d55f4bb03ae5b08e641c3c3a288c3981551079a
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