Instructions to use Viggle/Meridian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Viggle/Meridian with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Viggle/Meridian", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download MODIFICATIONS.md from Viggle/Meridian: direct link, hf CLI and curl.
- Browser
- Download file 4.65 kB
-
https://huggingface.co/Viggle/Meridian/resolve/main/MODIFICATIONS.md
- Command line
-
hf download hf://Viggle/Meridian/MODIFICATIONS.md
-
curl -L -o MODIFICATIONS.md https://huggingface.co/Viggle/Meridian/resolve/main/MODIFICATIONS.md
Modified files
Section III.2 of the MiniMax H3 Community License Agreement requires that modified files carry a prominent notice saying so. This file is that notice.
Everything below is derived from MiniMaxAI/MiniMax-H3.
teacher_lora/pytorch_lora_weights.safetensors β new
Not a MiniMax file, and it modifies none. A rank-128 LoRA over the linear layers of the base model's
transformer/, trained by us on a re-camera objective (source clip + a point-cloud render from a second
camera β that camera's clip). The base transformer/ is loaded unchanged from MiniMax and this is
applied on top of it as a live adapter; nothing is baked into the base weights. Its sampling grid is
--steps 50 --flow-shift 12.
turbo_lora/pytorch_lora_weights.safetensors β new
Not a MiniMax file. A rank-128 LoRA of the same shape, trained by us with DMD distillation. It is a delta
on the base plus the adapter above, not on the base alone, so the two are always loaded together. Its
sampling grid is --steps 4 --flow-shift 3.
legacy/transformer/ β modified
The first release shipped a transformer instead of adapters, and those files are still distributed here.
Every weight file in legacy/transformer/ has been modified. It started as the base model's
transformer/ (the fl2va video transformer, 50 layers) and every parameter was updated by a full
finetune on the re-camera objective above. The architecture, config.json and tensor names are unchanged,
so it is a drop-in replacement for the base transformer/; the numbers in it are not the base model's
numbers.
The file layout also differs: the finetune was written as one 61.7 GiB safetensors file and re-sharded here, because HuggingFace rejects single files above 50 GB. The tensors and their contents are unchanged by that re-sharding.
legacy/lora/pytorch_lora_weights.safetensors β new
Not a MiniMax file. A rank-128 DMD distillation of legacy/transformer/, and a delta on it specifically:
loading it onto the stock transformer/ produces garbage. Superseded by turbo_lora/.
assets/fixed_embed_{n}.pt, assets/silence_audio_{n}.pt β new
Not MiniMax files. Frozen text-conditioning tensors (one per supported output length) computed once
with the base model's own text encoder from the prompt in assets/prompt.txt, so that inference never
loads Qwen3-VL, and the audio latent of silence at each length. They are outputs of the base model's
encoders in the sense of Section I.12.
assets/prompt.txt β new
Not a MiniMax file. The prompt text the embeddings above were computed from, included so that what conditions every render is readable rather than opaque.
recam/, inference/, service/ β new
Not MiniMax files. Written by us against the public diffusers API (recam/h3.py calls the pipeline's
own layout builder and scheduler; nothing in diffusers is patched). Licensed under Apache 2.0
(LICENSE-CODE); each Python file carries an SPDX-License-Identifier: Apache-2.0 header.
comfyui/ β new
Not MiniMax files. comfyui/meridian_*_lora.safetensors are the two adapters above rewritten into
ComfyUI's generic LoRA layout by recam/to_comfyui.py β the same numbers in different keys, with the
qkv projections fused and the SwiGLU halves reordered to match, nothing retrained. They load on
ComfyUI's own minimax_h3_fl2va_bf16.safetensors, which is not redistributed here.
comfyui/meridian_embed.py and comfyui/meridian_geometry.py are ComfyUI nodes we wrote, and
comfyui/meridian_workflow*.json two graphs that wire them up β Apache 2.0 like the rest of the code.
Not included: VGGT-Omega
Inference depends on Meta's VGGT-Omega for geometry. It is not redistributed here (FAIR Noncommercial
Research License, gated weights); recam/geometry.py imports it from a path you provide. See README.md.
LICENSE, LICENSE-CODE, NOTICE
LICENSE is the MiniMax H3 Community License Agreement, included unmodified as Section III.1 requires.
LICENSE-CODE is the Apache 2.0 text and covers the code directories only. NOTICE records the
attribution and that the weights are not Apache 2.0.
Sampling draws every noise tensor on the CPU from the seeded generator, so a --seed reproduces across
GPU models. The internal tooling drew them in a different order and on the device, so a seed does not
reproduce a take made with it.
examples/media/ β new
Two clips from Wikimedia Commons under CC0, cut to 73 frames at 1280 Γ 720 with the soundtrack removed.
Provenance in examples/CREDITS.md. Not MiniMax material.