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Browse files- README.md +57 -7
- app.py +186 -0
- requirements.txt +2 -0
README.md
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---
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title: MiniMax
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colorFrom:
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sdk:
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---
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---
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title: MiniMax-H3 Character Swap LoRA
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emoji: π
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colorFrom: purple
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colorTo: pink
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sdk: gradio
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sdk_version: 5.49.1
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app_file: app.py
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short_description: Prompt + workflow demo for H3 character swap
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python_version: "3.12"
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license: other
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tags:
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- video-to-video
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- character-swap
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- minimax-h3
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- lora
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- comfyui
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models:
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- akatz-ai/MiniMax-H3-Character-Swap-LoRA
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- Comfy-Org/MiniMax-H3
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datasets:
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- akatz-ai/H3-Character-Swap-v1
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---
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# MiniMax H3 Character Swap LoRA β demo Space
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Interactive prompt builder and ComfyUI checklist for
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[akatz-ai/MiniMax-H3-Character-Swap-LoRA](https://huggingface.co/akatz-ai/MiniMax-H3-Character-Swap-LoRA).
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This Space does **not** run the H3 Ref2VA base model. That adapter is not a
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standalone generator: you still need the pruned INT8 Ref2VA checkpoint, the
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video/audio VAEs, and an H3 Ref2VA runtime (typically ComfyUI). Inference
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Providers do not currently host this model.
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What this demo does:
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1. Take a source-clip description and a replacement-character description
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2. Emit the card-recommended Ref2VA prompt (`<Video 1>` / `<Picture 1>`)
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3. Print a one-page ComfyUI setup sheet at LoRA strength **1.0**
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## Weights
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- LoRA: `h3_character_swap_pro4500_1000.safetensors` (final 1,000-step only)
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- Strength: **1.0**
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- No trained trigger word
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- Base: `minimax_h3_ref2va_pruned_int8_convrot.safetensors` from
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[Comfy-Org/MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3)
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- Training assistant (not merged): [ostris/minimax_h3_training_adapter](https://huggingface.co/ostris/minimax_h3_training_adapter)
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## License
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Distributed under the MiniMax H3 Community License Agreement. It is **not**
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Apache-2.0. Read the full terms on the model repo before commercial or
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territorial use.
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## Author notes from the card
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Short continuous 4β5 s shots at 24 fps work better than long 14 s tests.
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Hard cuts, facial-expression lock, and multi-character swaps are unreliable.
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This LoRA does not require a Turbo LoRA, Spectrum, or Sol attention.
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app.py
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"""MiniMax H3 Character Swap LoRA β prompt + workflow demo.
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This Space does not load the H3 base weights. It builds the Ref2VA prompt
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and ComfyUI checklist from the published model card.
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"""
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from __future__ import annotations
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import gradio as gr
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LORA_REPO = "https://huggingface.co/akatz-ai/MiniMax-H3-Character-Swap-LoRA"
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LORA_FILE = "h3_character_swap_pro4500_1000.safetensors"
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DATASET = "https://huggingface.co/datasets/akatz-ai/H3-Character-Swap-v1"
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BASE = "https://huggingface.co/Comfy-Org/MiniMax-H3"
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DEFAULT_TARGET = "the man in the purple shirt"
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DEFAULT_KEEP = (
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"Keep the replacement character's identity, outfit, and art style from <Picture 1>. "
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"Preserve the source video's camera, background, lighting, objects, and all other people. "
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"Match the target person's position, scale, pose, and movement. "
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"Do not show the reference sheet or its background."
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)
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SHORT_CAPTION = (
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"Swap {target} in <Video 1> with the character in <Picture 1>."
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)
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LONG_PROMPT = (
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"Replace only {target} in <Video 1> with the character in <Picture 1>. "
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"{keep}"
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)
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def build_pack(
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target: str,
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extra_keep: str,
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duration_s: float,
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fps: int,
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strength: float,
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use_long: bool,
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) -> tuple[str, str, str]:
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"""Build the Ref2VA prompt and a ComfyUI run sheet."""
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target = (target or DEFAULT_TARGET).strip()
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keep = (extra_keep or DEFAULT_KEEP).strip()
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prompt = LONG_PROMPT.format(target=target, keep=keep) if use_long else SHORT_CAPTION.format(target=target)
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sheet = f"""# H3 Character Swap β run sheet
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## Weights
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- LoRA: `{LORA_FILE}`
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- Repo: {LORA_REPO}
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- Strength: {strength:.2f} (card default: 1.00)
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- Trigger word: none
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- Turbo / Spectrum / Sol: not required
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## Base runtime (not bundled in this Space)
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- Diffusion: `minimax_h3_ref2va_pruned_int8_convrot.safetensors`
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- Source: {BASE}
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- Video + audio VAEs from the same org pack
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- Loader: model-only LoRA loader on the H3 transformer
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## Inputs
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- `<Video 1>` = source clip (prefer one continuous shot)
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- `<Picture 1>` = replacement character or sheet (no sheet background in the output)
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- Prompt below, verbatim
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## Timing
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- Duration request: {duration_s:.1f} s
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- Frame rate: {fps} fps
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- Card finding: 4β5 s continuous shots beat ~14 s tests
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- Hard cuts often become zooms or slides β trim cuts first
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## Limits (from the trainer)
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- Background preservation is the advertised win vs base Ref2VA
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- Expressions and cut timing are still unreliable
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- Multi-character replacement was not supervised
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- Audio from the model is not trustworthy; remux source audio after if needed
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"""
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checklist = f"""1. Drop `{LORA_FILE}` into `ComfyUI/models/loras/`
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2. Load H3 Ref2VA INT8 + VAEs (not this LoRA alone)
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3. Apply LoRA at strength {strength:.2f} with a model-only loader
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4. Wire source video β `<Video 1>`, character image β `<Picture 1>`
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5. Paste the prompt
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6. Generate a short 24 fps window, then continue if the join holds
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7. If lips drift, copy original audio onto the new video in post
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"""
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return prompt, sheet, checklist
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def preview_note(video, image) -> str:
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v = "source video attached" if video else "no source video yet"
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i = "reference image attached" if image else "no reference image yet"
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return (
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f"Local preview only β this Space does **not** run MiniMax H3.\n"
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f"- {v}\n- {i}\n\n"
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f"Take both files into ComfyUI with the generated prompt."
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)
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with gr.Blocks(title="MiniMax H3 Character Swap LoRA") as demo:
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gr.Markdown(
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f"""
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# MiniMax H3 Character Swap LoRA
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Experimental **one-character** replacement adapter by Akatz Labs
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([model card]({LORA_REPO}), [dataset]({DATASET})).
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Upload a clip and a character still, describe who to replace, and this demo
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writes the Ref2VA prompt plus a ComfyUI checklist. **Live H3 inference is not
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hosted here** β the adapter is 155 MB, the base Ref2VA stack is not, and no
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Inference Provider serves it yet.
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"""
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)
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with gr.Row():
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with gr.Column():
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video = gr.Video(label="Source clip β <Video 1>")
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image = gr.Image(type="filepath", label="Replacement character β <Picture 1>")
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target = gr.Textbox(
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label="Who to replace in the clip",
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value=DEFAULT_TARGET,
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placeholder="the woman in the red coat / the boy on the left / β¦",
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)
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extra_keep = gr.Textbox(
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label="Preservation instructions",
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value=DEFAULT_KEEP,
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lines=5,
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)
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with gr.Row():
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duration = gr.Slider(2, 14, value=5, step=0.5, label="Clip window (seconds)")
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fps = gr.Slider(8, 30, value=24, step=1, label="FPS")
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strength = gr.Slider(0.2, 1.2, value=1.0, step=0.05, label="LoRA strength")
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use_long = gr.Checkbox(
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value=True,
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label="Use the long preservation prompt (recommended in local evals)",
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)
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go = gr.Button("Build prompt + run sheet", variant="primary")
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with gr.Column():
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status = gr.Markdown("Attach a clip and a still, then build the pack.")
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prompt_out = gr.Textbox(label="Ref2VA prompt", lines=8)
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sheet_out = gr.Markdown()
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check_out = gr.Textbox(label="ComfyUI checklist", lines=10)
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go.click(
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preview_note,
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inputs=[video, image],
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outputs=status,
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).then(
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build_pack,
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inputs=[target, extra_keep, duration, fps, strength, use_long],
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outputs=[prompt_out, sheet_out, check_out],
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)
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gr.Examples(
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examples=[
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[
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"the man in the purple shirt",
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DEFAULT_KEEP,
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5.0,
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24,
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1.0,
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True,
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],
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[
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"the woman speaking on the left",
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DEFAULT_KEEP,
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4.0,
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24,
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1.0,
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True,
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],
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],
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inputs=[target, extra_keep, duration, fps, strength, use_long],
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label="Starter targets",
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)
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gr.Markdown(
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f"""
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---
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**Base model** is [Comfy-Org/MiniMax-H3]({BASE}), not merged into the LoRA.
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License: MiniMax H3 Community License β read it before you ship anything.
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"""
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)
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if __name__ == "__main__":
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demo.launch(mcp_server=True)
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requirements.txt
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# Gradio / spaces / huggingface_hub are preinstalled on Spaces.
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# Keep this file tiny so a CPU or ZeroGPU Space can boot.
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