Add deployment guides for Qwen3 and Qwen3 FP8 models on SageMaker

[shrimpnoodles]

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[gemini-code-assist]

Summary of Changes

Hello @shrimpnoodles, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces comprehensive documentation for deploying Qwen3 large language models on AWS SageMaker. It provides two distinct guides: one for the full-precision Qwen3 model and another for its FP8 quantized counterpart. The guides detail the necessary AWS infrastructure, Docker image preparation with vLLM, specific environment configurations for optimal performance, and practical steps for deployment, inference, and resource management.

Highlights

• New Deployment Guides: Introduced two comprehensive guides for deploying Qwen3 and Qwen3 FP8 models on AWS SageMaker, leveraging vLLM and Docker for efficient inference.
• Hardware and Instance Recommendations: Detailed hardware requirements, including specific GPU architectures (Ada Lovelace, Hopper, Ampere) for FP8 models and general GPU compute capabilities for full-precision models. Recommended AWS instance types like ml.g6.48xlarge with justifications for GPU count based on Qwen3's GQA architecture.
• vLLM Configuration: Provided specific vLLM environment variable configurations for each model variant, including tensor parallel size, maximum model length, GPU memory utilization, and enabling expert parallelism for FP8 models.
• End-to-End Deployment Workflow: Outlined a complete deployment strategy covering IAM permissions, Python dependencies, Docker image setup, ECR integration, SageMaker model deployment, example inference requests, and resource cleanup.
• Troubleshooting Section: Included dedicated troubleshooting tips for common issues such as memory errors, tensor parallel errors, and container startup timeouts, with actionable solutions.

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[gemini-code-assist]

Code Review

This pull request adds two comprehensive and well-structured deployment guides for Qwen3 and Qwen3 FP8 models on AWS SageMaker. The guides are a valuable addition, covering everything from hardware requirements to deployment and troubleshooting. I've included a few minor suggestions to address some inconsistencies in the Docker setup instructions and troubleshooting sections, which will help improve the clarity and accuracy for users. Overall, this is an excellent contribution.

[shrimpnoodles]

Comments reviewed, ready to be merged