Instructions to use NamCyan/graphcodebert-base-technical-debt-code-tesoro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NamCyan/graphcodebert-base-technical-debt-code-tesoro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NamCyan/graphcodebert-base-technical-debt-code-tesoro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NamCyan/graphcodebert-base-technical-debt-code-tesoro") model = AutoModelForSequenceClassification.from_pretrained("NamCyan/graphcodebert-base-technical-debt-code-tesoro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad3f5bb5dae681b9fd351de1ecd844e67de3a1a14fedb9cb4c71b1c897880943
- Size of remote file:
- 499 MB
- SHA256:
- 5824348bceb0c76fdc3c5b26435aea38a5ebcf55109097fad2f65d9205550503
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