Instructions to use 0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from 0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd: direct link, hf CLI and curl.
- Browser
- Download file 865 MB
-
https://huggingface.co/0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd/resolve/main/adapter_model.bin
- Command line
-
hf download hf://0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/0x1202/9a8ca2d8-f627-4801-9f82-83118641eafd/resolve/main/adapter_model.bin
865 MB
- Xet hash:
- c9e7e824ce3536af64aad28c8297d448e40b88423cda3fe5051c3eff1e41a1ff
- Size of remote file:
- 865 MB
- SHA256:
- f1461395037beb3a7975ce847d47a65a4ba824c54ca2d19b138797969299a1e1
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