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: 422 Bytes
adef9f2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | 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
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