Instructions to use goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d 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, "goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d/resolve/main/training_args.bin
- Command line
-
hf download hf://goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/goodlucky55555/bd05bd35-d781-43d9-a29a-086699a9fc9d/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- a74b5f3096aaefba88d40323f4454627938fcfb7681b4e8b7ce90b0d6f6be022
- Size of remote file:
- 6.78 kB
- SHA256:
- 8b235a6f3e8dd78a85bf56f3960114369a10bc383185b3924bf8ec7535118af2
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