metadata
license: other
license_name: minimax-h3-community-license-agreement
license_link: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE
tags:
- checkpoints
- minimax-h3
Checkpoints
MiniMax-H3
Mirror of MiniMaxAI/MiniMax-H3, in its native per-partition layout. Each variant folder is self-contained (transformer + text encoder + video/audio VAE + tokenizer + processor), so download only the one you need.
| Folder | Upstream partition | Tasks | Size |
|---|---|---|---|
MiniMax-H3/TI2V/ |
FL2VA |
T2VA (text-to-video+audio), FL2VA / I2VA (first/last-frame image-to-video+audio) | ~144 GB |
MiniMax-H3/Ref2V/ |
Ref2VA |
Ref2VA (reference-to-video+audio) | ~144 GB |
Layout of each variant:
transformer/ MiniMaxH3DiTModel, 13 safetensors shards
text_encoder/ Qwen3-VL encoder, 14 safetensors shards
video_vae/ video VAE code + source/model.safetensors
audio_vae/ audio VAE code + model.safetensors
tokenizer/ processor/ model_index.json LICENSE
Download one variant
# T2V / I2V
hf download mingyang-wu/Checkpoints --repo-type dataset \
--include "MiniMax-H3/TI2V/*" --local-dir ./ckpts
# Ref2V
hf download mingyang-wu/Checkpoints --repo-type dataset \
--include "MiniMax-H3/Ref2V/*" --local-dir ./ckpts
Only the transformer weights (skip the shared text encoder / VAE you already have):
hf download mingyang-wu/Checkpoints --repo-type dataset \
--include "MiniMax-H3/Ref2V/transformer/*" --local-dir ./ckpts
Python:
from huggingface_hub import snapshot_download
path = snapshot_download("mingyang-wu/Checkpoints", repo_type="dataset",
allow_patterns="MiniMax-H3/Ref2V/*", local_dir="./ckpts")
# -> ./ckpts/MiniMax-H3/Ref2V
The weights are distributed under the MiniMax-H3 Community License (see LICENSE inside each variant folder).