Accelerate multimodal RL training with SkyRL on Amazon SageMaker HyperPod
How-To How to actually use this
What changed: A new walkthrough shows how to run the open-source SkyRL framework on SageMaker HyperPod to post-train Qwen3-VL-8B with GRPO.
How to use it:
- Build the SkyRL container image with required dependencies for vision-language RL training.
- Launch a Ray cluster from SageMaker Studio using the HyperPod cluster configuration.
- Submit the GRPO training job targeting the Qwen3-VL-8B model with your dataset.
- Monitor training progress and resource utilization via the Ray dashboard in Studio.
- Deploy the resulting LoRA adapter for inference using the provided hosting instructions.
Good for: ML engineers post-training vision-language models with RL.
Learn how to run SkyRL, an open-source reinforcement learning framework, on Amazon SageMaker HyperPod to post-train a Qwen3-VL-8B vision-language model with GRPO. This walkthrough covers building the container image, launching a Ray cluster from SageMaker Studio, submitting and monitoring the job, and hosting the trained LoRA adapter for inference.
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