Instructions to use Non-SHADovcy/synthetic-cpp-code-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Non-SHADovcy/synthetic-cpp-code-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Non-SHADovcy/synthetic-cpp-code-detection", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Non-SHADovcy/synthetic-cpp-code-detection", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import PretrainedConfig | |
| class CustomConfig(PretrainedConfig): | |
| model_type = "custom_model" | |
| def __init__(self, | |
| transformer_type = "microsoft/graphcodebert-base", | |
| transformer_output_dim = 768, | |
| **kwargs): | |
| super().__init__(**kwargs) | |
| self.transformer_type = transformer_type | |
| self.transformer_output_dim = transformer_output_dim | |