| --- |
| title: MiniMax-H3-Fun-Controlnet-Union |
| description: Showcase Space for the MiniMax-H3-Fun-Controlnet-Union model — a single ControlNet-Union checkpoint for Canny, Depth, HED, MLSD, and Pose control on MiniMax-H3 video generation. |
| tags: |
| - controlnet |
| - video-generation |
| - minimax-h3 |
| - video-to-video |
| - gradio |
| --- |
| |
| # MiniMax-H3-Fun-Controlnet-Union — Hugging Face Space |
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| A showcase Space for the [MiniMax-H3-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/MiniMax-H3-Fun-Controlnet-Union) model by alibaba-pai. |
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| ## What is this? |
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| MiniMax-H3-Fun-Controlnet-Union is a **ControlNet-Union** checkpoint for the [MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3) video diffusion transformer. One single checkpoint handles **Canny, Depth, HED, MLSD, and Pose** control conditions for video-to-video generation — no per-condition checkpoint switching — and also supports video inpainting. |
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| The control branch (~6.8 GB) is loaded on top of the base MiniMax-H3 transformer and injects control signals at 5 points (layers 0, 10, 20, 30, 40) of the 50-block architecture. |
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| ## Space contents |
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| This Space shows: |
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| - **Model overview** — description, file table, and key features |
| - **Inference defaults** — the settings used for all published results |
| - **5 result pairs** — control input + generated output for each control type (Canny, Depth, HED, MLSD, Pose), sourced directly from the model repo |
| - **Setup guide** — how to run inference via the [VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun) pipeline |
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| ## Inference requirements |
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| Running the actual model requires: |
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| - The base **MiniMax-H3** transformer (~62 GB) |
| - The **Qwen3-VL** text encoder (~62 GB) |
| - This ControlNet-Union checkpoint (~6.8 GB) |
| - VideoX-Fun installed with the matching `minimax_h3_control.yaml` config |
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| The full model does **not** fit a single 80 GB GPU fully loaded — use `model_group_offload` or `model_cpu_offload_and_qfloat8`. |
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| See the Space app for the full step-by-step inference guide. |
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