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jiayanmu PRO

wangbuer999

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HunyuanImage 3.0-Instruct just dropped fresh -sourceImage 3.0model! Spent 20 mins testing it on a Messi + retro scrambler fusion case Ran on diffusers v0.26.3 + CUDA 12.1 | 8B MoE params (1.3B activated) | zero VRAM issues strength=0.9 Messi #10 kit/tattoo sharp, moto’s rusted metal texture blurred (classic open-source pain) strength=0.7 Moto/cobblestone background crisp, Messi’s jersey details faded completely strength=0.75 + prompt "Blend seamlessly, keep all original details": both subject & background sharp No ControlNet, no manual masking the model’s chain-of-thought reasoning parses image+prompt first Already outperforms Qwen-Image-Edit 2511 (GSB eval +25.7% on single-image edits) | 100% open-source 👉 Repo: https://hunyuan.tencent.com/chat/HunyuanDefault?from=modelSquare&modelId=Hunyuan-Image-3.0-Instruct technical report：https://arxiv.org/abs/2509.23951 Anyone else struggled with strength tweaks for fusion? This fixed it for my Messi+moto case did it work as well for yours?

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HunyuanImage 3.0-Instruct just dropped

fresh -sourceImage 3.0model! Spent 20 mins testing it on a Messi + retro scrambler fusion case

Ran on diffusers v0.26.3 + CUDA 12.1 | 8B MoE params (1.3B activated) | zero VRAM issues

strength=0.9 Messi #10 kit/tattoo sharp, moto’s rusted metal texture blurred (classic open-source pain)
strength=0.7 Moto/cobblestone background crisp, Messi’s jersey details faded completely

strength=0.75 + prompt "Blend seamlessly, keep all original details": both subject & background sharp
No ControlNet, no manual masking the model’s chain-of-thought reasoning parses image+prompt first
Already outperforms Qwen-Image-Edit 2511 (GSB eval +25.7% on single-image edits) | 100% open-source

👉 Repo: https://hunyuan.tencent.com/chat/HunyuanDefault?from=modelSquare&modelId=Hunyuan-Image-3.0-Instruct

technical report：https://arxiv.org/abs/2509.23951

Anyone else struggled with strength tweaks for fusion? This fixed it for my Messi+moto case did it work as well for yours?

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3218

HY-MT1.5-1.8B Lightweight Translation Model Open-Source Game-Changer

Tencent raised the bar for lightweight translation!

Supports bidirectional translation across 36 languages total—33 mainstream languages + 5 ethnic/minority dialects

With only 1.8B parameters (less than 1/3 the size of HY-MT1.5-7B), it delivers performance on par with the 7B counterpart and outperforms most commercial translation APIs.

✅ Quantized versions (FP8/GPTQ-Int4) available for edge device deployment, perfect for real-time translation
✅ Full support for terminology intervention, context-aware translation, and formatted output
✅ Ready-to-use prompt templates + seamless integration with Hugging Face Transformers
✅ Recommended transformers ≥ 4.56.0 (FP8 model requires compressed-tensors 0.11.0)

10+ Hugging Face Spaces already integrated this model!

👉 Model Repo: tencent/HY-MT1.5-1.8B
👉 Technical Report: https://arxiv.org/abs/2512.24092

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