Instructions to use zcahjl3/STORY_ERROR_CLASSIFICATION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcahjl3/STORY_ERROR_CLASSIFICATION with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zcahjl3/STORY_ERROR_CLASSIFICATION")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION") model = AutoModelForSequenceClassification.from_pretrained("zcahjl3/STORY_ERROR_CLASSIFICATION", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Training in progress, epoch 5
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Training in progress, epoch 4
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Training in progress, epoch 3
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Training in progress, epoch 2
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Training in progress, epoch 1
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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