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| Multi-Modal Example Architecture | |
| ================================= | |
| Last updated: 04/28/2025. | |
| Introduction | |
| ------------ | |
| Now, verl has supported multi-modal training. You can use fsdp and | |
| vllm/sglang to start a multi-modal RL task. Megatron supports is also | |
| on the way. | |
| Follow the steps below to quickly start a multi-modal RL task. | |
| Step 1: Prepare dataset | |
| ----------------------- | |
| .. code:: python | |
| # it will be saved in the $HOME/data/geo3k folder | |
| python examples/data_preprocess/geo3k.py | |
| Step 2: Download Model | |
| ---------------------- | |
| .. code:: bash | |
| # download the model from huggingface | |
| python3 -c "import transformers; transformers.pipeline(model='Qwen/Qwen2.5-VL-7B-Instruct')" | |
| Step 3: Perform GRPO training with multi-modal model on Geo3K Dataset | |
| --------------------------------------------------------------------- | |
| .. code:: bash | |
| # run the task | |
| bash examples/grpo_trainer/run_qwen2_5_vl-7b.sh | |