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:
- 76d3754216cadd811e77827bab7ffad961df492c54cadb8a0da20c4269933b7e
- Size of remote file:
- 5.05 kB
- SHA256:
- 2e87bd65f7bf60784b57aa5595442b3e98ecb09b699072dec517d350a12ff843
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