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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("azherali/CodeGenDetect-CodeBert_Lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from azherali/CodeGenDetect-CodeBert_Lora: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/azherali/CodeGenDetect-CodeBert_Lora/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://azherali/CodeGenDetect-CodeBert_Lora/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/azherali/CodeGenDetect-CodeBert_Lora/resolve/main/adapter_model.safetensors
3.56 MB
- Xet hash:
- e2ee693b92b0873b7a79e38ba2355b0f25924df0e7a03a6b7cd3c7b210289d51
- Size of remote file:
- 3.56 MB
- SHA256:
- 926ed83f6e74d30dd04cd576ac59c6374f40022ad71666f1151acf89ef6a727f
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