akatz-ai/MiniMax-H3-Character-Swap-LoRA

video-to-video model by akatz-ai

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[](https://x.com/akatzai) [](https://www.patreon.com/Akatz) [](https://github.com/sponsors/akatz-ai) [](https://ko-fi.com/akatz) Original → Reference → Character swap. Four selected examples. V1.5 is the recommended checkpoint for new character swaps. It replaces a selected person in a source performance with a character from an image reference. existing workflows and reproducible comparisons. Download the canvas workflow or the API prompt. These use the recommended V1.5 adapter, native ComfyUI model loading, reference conditioning, SAM masking, sampling, loops and saving, plus reusable Relay timeline helpers. The model weights are unchanged by this workflow update. Install H3 Relay 2.0 and follow the workflow guide for models, runtime and input paths. and select it in a compatible model-only LoRA loader at strength 1.0. . Describe the person to replace and the reference identity. frame grid and review identity, motion, expressions and joins before extending. Example: The H3 Character Swap tool handles masks, optional scene anchors, source-audio conditioning and continuation history. Its tested recipe…

akatz-ai/MiniMax-H3-Character-Swap-LoRA on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-11-10T09:38:37.637Z

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Model overview

akatz-ai/MiniMax-H3-Character-Swap-LoRA is a video-to-video model repository published by akatz-ai on Hugging Face. The source reports the diffusion-single-file library.

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Model facts

Task: video-to-video
Library: diffusion-single-file
Recent downloads (30 days): 143,978
Cumulative likes: 957
Hugging Face trending score: 149
Reported safetensors parameters: Not reported
Architecture: Not reported
License: other
Access: Not gated by Hugging Face
Created: 2026-09-25T08:14:15.000Z
Last modified: 2026-10-17T23:41:56.000Z

Compatibility and lineage

Reported languages: en

Reported base models: Comfy-Org/MiniMax-H3

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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