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Check out the documentation for more information.
HIL Code LlamaFactory Setup
Reproduce Setup
LlamaFactory expects custom local datasets under its data/ directory, registered in data/dataset_info.json, and example training YAMLs under examples/.
uv venv .venv/hil-code --python=3.12
source .venv/hil-code/bin/activate
git clone https://github.com/hiyouga/LlamaFactory.git LlamaFactory
uv pip install -e ./LlamaFactory -r LlamaFactory/requirements/metrics.txt
uv pip install -r LlamaFactory/requirements/galore.txt -r LlamaFactory/requirements/badam.txt
cp data/hil_code_dpo.json LlamaFactory/data/hil_code_dpo.json
cp data/dataset_info.json LlamaFactory/data/dataset_info.json
cp examples/train_lora/qwen36_lora_dpo.yaml LlamaFactory/examples/train_lora/qwen36_lora_dpo.yaml
The local config uses template: qwen3_5 because this LlamaFactory revision does not define a qwen3_6 template, and Qwen/Qwen3.6-27B is handled through the Qwen3.5 model family path.
Train
Run from the workspace root:
mkdir -p .cache/matplotlib
source .venv/hil-code/bin/activate
MPLCONFIGDIR="$PWD/.cache/matplotlib" CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 llamafactory-cli train LlamaFactory/examples/train_lora/qwen36_lora_dpo.yaml
For multi-GPU CUDA/Linux training of the 27B model, install the platform-specific extras in the same venv on the target machine:
source .venv/hil-code/bin/activate
uv pip install -r LlamaFactory/requirements/deepspeed.txt
uv pip install -r LlamaFactory/requirements/liger-kernel.txt
References:
- LlamaFactory docs: https://llamafactory.readthedocs.io/en/latest/
- LlamaFactory data format notes:
LlamaFactory/data/README.md - LlamaFactory DPO docs:
LlamaFactory/docs/en/training/dpo.md
To avoid the influences of special tokens that contained in the code, please use the following commands to run the training
IMAGE_PLACEHOLDER='<>'
VIDEO_PLACEHOLDER='<>'
AUDIO_PLACEHOLDER='<>'
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 .venv/hil-code/bin/llamafactory-cli train
LlamaFactory/examples/train_lora/qwen36_lora_dpo.yaml
IMAGE_PLACEHOLDER='<>'
VIDEO_PLACEHOLDER='<>'
AUDIO_PLACEHOLDER='<>'
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 .venv/hil-code/bin/llamafactory-cli train
LlamaFactory/examples/train_lora/qwen36_lora_sft.yaml
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