Instructions to use larryvrh/MiniMax-H3-Turbo-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -38,9 +38,18 @@ Custom nodes: **[Larryvrh/ComfyUI-MiniMax-H3-Turbo](https://github.com/Larryvrh/
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- replace the sampler feeding `SamplerCustomAdvanced` with **MiniMax-H3 Turbo
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Sampler (4-step)**, and set the scheduler to **4 steps** (`simple`).
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Everything else stays as in the official workflow, so both t2v and i2v work.
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## Weights
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- replace the sampler feeding `SamplerCustomAdvanced` with **MiniMax-H3 Turbo
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Sampler (4-step)**, and set the scheduler to **4 steps** (`simple`).
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Everything else stays as in the official workflow, so both t2v and i2v work. A
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ready-made t2v workflow is included here (`minimax_h3_t2v_turbo.json`) and in the
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[node repo](https://github.com/Larryvrh/ComfyUI-MiniMax-H3-Turbo/tree/main/example_workflows)
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— drag it into ComfyUI. The custom sampler is required: MiniMax-H3 runs video and
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audio on two different flow schedules, and a stock sampler over-steps the audio
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at 4 steps and it breaks.
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- **Steps**: any count **≥ 4** works and **more steps look better** — 4 is the
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fast default, 6 or 8 are cleaner. Keep the scheduler on `simple`.
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- **Base model**: use a **non-pruned** base (the `bf16` or full `int8_convrot`
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DiT). The **pruned** variants (`pruned_int8`, `pruned_fp8`) use a different
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time-conditioning layer and are **not compatible** with this LoRA.
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## Weights
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