Instructions to use burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-12B-it") model = PeftModel.from_pretrained(base_model, "burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback: direct link, hf CLI and curl.
- Browser
- Download file 131 MB
-
https://huggingface.co/burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/burtenshaw/gemma-4-12b-sdpo-pi-mono-trace-feedback/resolve/main/adapter_model.safetensors
131 MB
- Xet hash:
- 2c36911dfdc2f80ec32aafd6e3e2292daf198aef60afd85b4f2f3f25719bf7ba
- Size of remote file:
- 131 MB
- SHA256:
- ee1068ce026bdb2501b423c486986b218a4201afd77ddcb639e63933c8e3cef5
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