Students Train SOTA Code Models on Single GPUs
Researchers demonstrate how students can train state-of-the-art code generation models on single consumer GPUs using novel optimization techniques and
Students replicate SOTA coding models using DeepSpeed optimizations on single GPUs.
Clone the Training Repository:
Enable DeepSpeed ZeRO-3 Offloading:
Add to deepspeed_config.json:
"zero_optimization": {
"stage": 3,
"offload_optimizer": {"device": "cpu"},
"offload_param": {"device": "cpu"}
}Launch Training:
Test on LiveCodeBench: Visit https://livecodebench.github.io/ for evaluation scripts.
Monitor Training:
- Press Ctrl+C to pause safely
- Use
nvidia-smito track VRAM usage
This setup reduced 14B parameter fine-tuning from 1.6 months to 2 weeks on a single A6000 GPU, achieving 41.7% Pass@1 by offloading optimizer states to CPU RAM.
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