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:
- ae92c7805038daf07dd7b10c854dc81c40d35cd435008535e51bbf827b299ca7
- Size of remote file:
- 7.14 MB
- SHA256:
- 118eb527e3f3d95f6bbf2dc9c4c0579763f722fb5753842653cc84555c706dc2
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