Instructions to use gongjae/graphcodebert-c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gongjae/graphcodebert-c with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gongjae/graphcodebert-c")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gongjae/graphcodebert-c") model = AutoModelForSequenceClassification.from_pretrained("gongjae/graphcodebert-c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ba9d3685cccbbbb55f76eab1982a61d354f2b593776d695e8e7eec67ac29f6d
- Size of remote file:
- 499 MB
- SHA256:
- 648fa510d53762cf2a5a8feb72440cfb9588797f0c85b879e4ad84b88bdd4042
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