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
| { | |
| "_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" | |
| } | |