Instructions to use uclanlp/plbart-c-cpp-defect-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-c-cpp-defect-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="uclanlp/plbart-c-cpp-defect-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-c-cpp-defect-detection") model = AutoModelForSequenceClassification.from_pretrained("uclanlp/plbart-c-cpp-defect-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adds tokenizer_config.json file
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Add spiece model and update config files
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Add model files
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initial commit
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