Instructions to use DongfuJiang/vapo_lora_all_data_iter_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DongfuJiang/vapo_lora_all_data_iter_2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct") model = PeftModel.from_pretrained(base_model, "DongfuJiang/vapo_lora_all_data_iter_2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DongfuJiang/vapo_lora_all_data_iter_2: direct link, hf CLI and curl.
- Browser
- Download file 6.58 kB
-
https://huggingface.co/DongfuJiang/vapo_lora_all_data_iter_2/resolve/main/training_args.bin
- Command line
-
hf download hf://DongfuJiang/vapo_lora_all_data_iter_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DongfuJiang/vapo_lora_all_data_iter_2/resolve/main/training_args.bin
6.58 kB
- Xet hash:
- e82ad13c379c7b786b97c5cca1815c7edcd4a036d4806c88832c6080ba1be7ae
- Size of remote file:
- 6.58 kB
- SHA256:
- 6b21a585eb369d64973dba1113a008637189ba9e429704a23efe75f18bc59f4b
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