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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 377 Bytes
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"_name_or_path": "best_model",
"architectures": [
"CombinedModel"
],
"auto_map": {
"AutoConfig": "model_config.CustomConfig",
"AutoModel": "model_arch.CombinedModel"
},
"model_type": "custom_model",
"torch_dtype": "float32",
"transformer_output_dim": 768,
"transformer_type": "microsoft/graphcodebert-base",
"transformers_version": "4.42.3"
}
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