Current Best settings for viggle 4step: er_sde/beta 5steps cfg 1 (+ lenovo lora to remove some of the overbaked, high contrast, yellow tint) All examples are generated with 1.0 strength I did not train, distill, or create the original Turbo LoRA weights. This model page provides only modified compatibility versions intended to let the remaining compatible LoRA adapters load with ComfyUI's built-in LoRA loader Full credit for the original Qwen-Image-2.1-viggle-turbo-4step-lora-r64.safetensors belongs to the <a target="_blank" rel="ugc" href="https://huggingface.co/Viggle">ViggleAI</a> Team. Viggle statement for v0.1: "Status: v0.1 preview, work in progress — this release still falls short of the base model. On complicated image editing (multi-reference composition, face swaps, identity-preserving edits, instructions with several constraints) it is clearly worse than the 40-step base model. Text-to-image at 4 steps is usable. We are still working on it and will update this repository as the distillation improves; treat the current weights as a preview, not a replacement for the base model."

Qwen 2.1 Turbo LoRas

Qwen-Image-2.1-viggle-turbo-4step-lora-r64.safetensors

Qwen_Viggle_4step_0.1

<h1 id="qw21-turbo-0.1-by-viggle">QW21-Turbo-0.1 by <a target="_blank" rel="ugc" href="https://viggle.ai/">Viggle</a></h1><h3 id="steps-4-16-cfg1-t2ii2i">Steps 4-16 CFG=1 T2i/i2i</h3>演示图片同时使用了 Viggle/Qwen-Image-2.1-viggle-turbo 和 REDQW21 UNLOCKED LoRA (with NV DLSS_NR) 仅作为[ 研究或评估 ]用途内使用 / only for the research or evaluation purposesThe demo images uses both Viggle/Qwen-Image-2.1-viggle-turbo and REDQW21 UNLOCKED LoRA simultaneously Built with Qwen, Applicable to Qwen-Image-2.1Viggle/Qwen-Image-2.1-viggle-turbo source repo: <a target="_blank" rel="ugc" href="https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo">https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo</a>All credit belongs to the original model author. License is the same as the original model.Model: <a target="_blank" rel="ugc" href="https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo">Viggle/Qwen-Image-2.1-viggle-turbo</a> · Built with Qwen — distilled from <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1">Qwen/Qwen-Image-2.1</a>, which is released under the <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE">Qwen RESEARCH LICENSE AGREEMENT</a> (non-commercial: research or evaluation purposes only).Built with Qwen. A 4-step distilled student of <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1">Qwen/Qwen-Image-2.1</a>, trained by Viggle with Distribution Matching Distillation. It does both text-to-image and instruction-driven editing with 1–3 reference images in 4 transformer passes instead of 40, with no classifier-free guidance.Two students are shipped — pick one:<ul><li><code>transformer/</code> — full fine-tuned transformer (bf16, 14.2 GB). Replaces the base transformer; exact, no adapter. This is what the <a target="_blank" rel="ugc" href="https://huggingface.co/spaces/Viggle/Qwen-Image-2.1-viggle-turbo">demo Space</a> runs by default and the one we currently recommend — in our qualitative comparison it edits more faithfully than the LoRA.</li><li><code>Qwen-Image-2.1-viggle-turbo-4step-lora-r64.safetensors</code> — LoRA adapter (rank 64, 340 MB) loaded on top of the base transformer at runtime. Smaller download, slightly weaker.</li></ul>Status: v0.1 preview, work in progress — this release still falls short of the base model. On complicated image editing (multi-reference composition, face swaps, identity-preserving edits, instructions with several constraints) it is clearly worse than the 40-step base model. Text-to-image at 4 steps is usable. We are still working on it and will update this repository as the distillation improves; treat the current weights as a preview, not a replacement for the base model.<hr /><h1 id="minimax-h3-turbo-by-lightx2v"><a target="_blank" rel="ugc" href="https://github.com/ModelTC/Minimax-H3-Turbo">Minimax-H3-Turbo by LightX2V</a></h1>Minimax-H3-Turbo provides batch MiniMax-H3 inference and NFE/LoRA comparisons.<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/85a4f8c1-9688-4bd7-ac02-0bb3af81bdf7/original=true/85a4f8c1-9688-4bd7-ac02-0bb3af81bdf7.jpeg" /><h2 id="repos">Repos</h2>Kijai/MiniMax-H3_comfy <a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/MiniMax-H3_comfy/tree/main/loras">Minimax-H3-Turbo ComfyUI v0.1</a>lightx2v/Minimax-h3-Turbo <a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Minimax-h3-Turbo/tree/main">Minimax-h3-Turbo Diffusers/ComfyUI v1.0</a><h2 id="note">Note</h2>Its current visual quality can be reviewed in the linked examples, and the image details still need improvement. An enhanced version is in development.<h3 id="this-edition-is-compatible-with-the-comfyui-pruned">This Edition is compatible with the ComfyUI-pruned</h3><h3 id="minimax-h3-fl2va-model20b.">MiniMax H3 FL2VA model（20B）.</h3><h2 id="roadmap">Roadmap</h2><ol><li>Improve the visual details and overall quality of FL2V Turbo.</li><li>Develop distillation based on Ref2V.</li></ol><h2 id="preview">Preview</h2><a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Minimax-h3-Turbo/discussions/2">https://huggingface.co/lightx2v/Minimax-h3-Turbo/discussions/2</a>Apache-2.0 license

[ Accelerator LoRAs ] Applicable to QW21 | Minimax H3 | HYVideo TURBO/LIGHTNING/DMD/FAST

Reposting from <a target="_blank" rel="ugc" href="https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo">https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo</a>All credit belongs to the original model author. License is the same as the original model.Model: <a target="_blank" rel="ugc" href="https://huggingface.co/Viggle/Qwen-Image-2.1-viggle-turbo">Viggle/Qwen-Image-2.1-viggle-turbo</a> · Built with Qwen — distilled from <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1">Qwen/Qwen-Image-2.1</a>, which is released under the <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE">Qwen RESEARCH LICENSE AGREEMENT</a> (non-commercial: research or evaluation purposes only).Built with Qwen. A 4-step distilled student of <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image-2.1">Qwen/Qwen-Image-2.1</a>, trained by Viggle with Distribution Matching Distillation. It does both text-to-image and instruction-driven editing with 1–3 reference images in 4 transformer passes instead of 40, with no classifier-free guidance.Two students are shipped — pick one:<ul><li><code>transformer/</code> — full fine-tuned transformer (bf16, 14.2 GB). Replaces the base transformer; exact, no adapter. This is what the <a target="_blank" rel="ugc" href="https://huggingface.co/spaces/Viggle/Qwen-Image-2.1-viggle-turbo">demo Space</a> runs by default and the one we currently recommend — in our qualitative comparison it edits more faithfully than the LoRA.</li><li><code>Qwen-Image-2.1-viggle-turbo-4step-lora-r64.safetensors</code> — LoRA adapter (rank 64, 340 MB) loaded on top of the base transformer at runtime. Smaller download, slightly weaker.</li></ul>Status: v0.1 preview, work in progress — this release still falls short of the base model. On complicated image editing (multi-reference composition, face swaps, identity-preserving edits, instructions with several constraints) it is clearly worse than the 40-step base model. Text-to-image at 4 steps is usable. We are still working on it and will update this repository as the distillation improves; treat the current weights as a preview, not a replacement for the base model.

Files with SHA256: 5c494dce662a95898d0988831af733b203ceced9116a82aa099c997f96ea1a3a