Instructions to use djroytburg/auditbench-llama33-70b-native-kto-co with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use djroytburg/auditbench-llama33-70b-native-kto-co with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.3-70B-Instruct") model = PeftModel.from_pretrained(base_model, "djroytburg/auditbench-llama33-70b-native-kto-co") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cb7a77fdd85182ac68b861724115c0c757966920712e0a9e3b8b9da81b87ad8
- Size of remote file:
- 6.63 GB
- SHA256:
- 1a6c21f9795c62294d284857889bf496ac21e96bbf7224d747cfa62c34ac4961
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