Instructions to use azherali/CodeGenDetect-CodeBert_Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use azherali/CodeGenDetect-CodeBert_Lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("microsoft/codebert-base") model = PeftModel.from_pretrained(base_model, "azherali/CodeGenDetect-CodeBert_Lora") - Transformers
How to use azherali/CodeGenDetect-CodeBert_Lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("azherali/CodeGenDetect-CodeBert_Lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2ee693b92b0873b7a79e38ba2355b0f25924df0e7a03a6b7cd3c7b210289d51
- Size of remote file:
- 3.56 MB
- SHA256:
- 926ed83f6e74d30dd04cd576ac59c6374f40022ad71666f1151acf89ef6a727f
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