Tencent-Hunyuan/SRPO

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1278 stars · 42 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SRPO is Tencent Hunyuan's research code for fine-tuning diffusion image generation models (e.g., FLUX.1.dev) by aligning the full diffusion trajectory with fine-grained human preference via online reward adjustment. It introduces Direct-Align sampling and Semantic Relative Preference Optimization for faster, more stable training without reward hacking.

Use cases

• fine-tune flux image generation for better realism
• align diffusion models with human aesthetic preference
• train text-to-image model with reward optimization
• improve photorealism of generated images
• avoid reward hacking in diffusion fine-tuning
• fast preference optimization for image models

When to choose

• you want to fine-tune FLUX or similar diffusion models with human preference rewards
• you need faster, cheaper reward-based diffusion training than GRPO or ReFL
• you want to avoid reward hacking without KL regularization

When to avoid

• you need a production image generation service rather than training code
• you work with non-diffusion generative models
• you lack GPU resources for diffusion model training

Facets

library · maturity active

machine-learning llm-training image-processing stable-diffusion deep-learning image-processing artificial-intelligence python diffusion-models fine-tuning human-preference-alignment reward-optimization flux research-code gpu linux

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