MiniMax-H3-Fun-Controlnet-Union-2.0.safetensors

Update:Sep 23, 2026 23:45|Published:Sep 23, 2026 23:45
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MiniMax-H3-Fun-Controlnet-Union-2.0.safetensors. --- license: other license link: LICENSE.md license name: minimax-h3-community-license-agreement library name: videox fun tags: - c…
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Gugugaga
Type
Controlnet
Basic Model
MiniMax H3
Published time
Sep 23, 2026 23:45
File Signature
404155870f4f2c4dcc1b632f7eb2ccffec82ea4cccf6298ae7b5abfd3623d141
MiniMax-H3-Fun-Controlnet-Union-2.0.safetensors
12.62 GB

license: other license_link: LICENSE.md license_name: minimax-h3-community-license-agreement library_name: videox_fun tags:

  • controlnet
  • controlnet-union
  • video-to-video
  • image-text-to-video
  • text-to-video
  • video-inpainting tasks:
  • text-to-video-synthesis

MiniMax-H3-Fun-Controlnet-Union-2.0

Github

What's new in 2.0

MiniMax-H3-Fun-Controlnet-Union (v1)MiniMax-H3-Fun-Controlnet-Union-2.0 (this model)
Control conditions5 — Canny, Depth, HED, MLSD, Pose8 — + Scribble, Layout, Gray
Control branch depth5 control blocks (layers 0, 10, 20, 30, 40)10 control blocks (layers 0, 5, 10, …, 45) — skips injected every 5 of the 50 transformer blocks
Inpaint masked-pixel recipepre_norm (holes ≈ −2 in VAE input space, extreme dark)post_norm (holes at 0, mid-gray, following Wan 2.1) — cleaner inpaint blending
Checkpoint contentscontrol_proj_in + 5 control_blocks (~6.8 GB)control_proj_in + 10 control_blocks (~13.5 GB)
Required configminimax_h3_control.yamlminimax_h3_control_inpaint_post_norm.yaml

Everything else is carried over from v1: control_in_dim = 49 (latent + masked latent + mask, so the same branch does control and inpaint), control_apply_audio = false, guidance-distilled (guidance_scale = 1.0), and the same zero-gated skip-add into the main branch.

Loading a v1 config against this checkpoint is a silent failure. With minimax_h3_control.yaml (5 blocks) the model builds only half the control branch; load_state_dict(strict=False) drops control_blocks.5~9 as unexpected keys and misplaces the rest, producing wrong outputs. Always use minimax_h3_control_inpaint_post_norm.yaml.

Model Card

NameDescription
MiniMax-H3-Fun-Controlnet-Union-2.0.safetensorsControlNet-Union-2.0 branch weights for MiniMax-H3. Holds only the control branch (control_proj_in plus 10 control_blocks, about 13.5 GB) and is loaded on top of the base MiniMax-H3 transformer. One checkpoint supports 8 control conditions (Canny, Depth, HED, MLSD, Pose, Scribble, Layout, Gray) and video inpainting.

Model Features

  • Union control over 8 conditions: one checkpoint handles Canny, Depth, HED, MLSD, Pose, Scribble, Layout and Gray control videos for video-to-video generation — no per-condition checkpoint switching.
  • Denser control injection: the control branch attaches to 10 of the 50 transformer blocks (layers 0, 5, 10, 15, 20, 25, 30, 35, 40, 45); every control skip is added to the main branch through a zero-gated projection. This is roughly 2× the injection points of v1 and gives tighter structural adherence.
  • Guidance-distilled: run with guidance_scale = 1.0, one forward pass per step, no classifier-free guidance needed.
  • Inpainting is supported, with the post_norm recipe: the control input is widened to control_in_dim = 49 (latent + masked latent + mask channels). Unlike v1, the masked pixels are zeroed after the ImageNet normalization (holes sit at 0 / mid-gray) rather than before it (holes landed near −2 / extreme dark), which improves how filled regions blend with kept regions. Use examples/minimax_h3_fun/predict_v2v_control_inpaint.py.
  • control_context_scale scales every control skip before it is added to the main branch: 1.0 gives the strongest control (used for all results below), values below 1.0 weaken the guidance of the control video, 0.0 switches the control branch off.
  • The generation follows the control video: the frame count snaps down to the largest 17 * n + 5 the video VAE can decode (duration capped at 15 seconds), the canvas keeps the control video's own aspect ratio at the height * width pixel budget (both multiples of 32), at a fixed 24 fps.
  • Detailed prompts give better stability; we recommend describing the scene, the subject and the camera in the prompt.

Supported control conditions

ConditionControl signalNew in 2.0?
CannyCanny edge map
DepthMonocular depth map
HEDHED edge detection
MLSDLine-segment detection
PoseDWPose skeleton
ScribbleFree-hand / sketch lines✅
LayoutBounding-box layout✅
GrayGrayscale (luminance) video✅

See the full description on the original page

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