---
title: Controllable Human Motion Generation
emoji: 🌍
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 6.15.0
python_version: '3.12'
app_file: app.py
pinned: false
license: mit
short_description: Style-SALAD human motion generation on ZeroGPU
---

# Style-SALAD Motion Studio

The interface follows Joao’s files: permanent navy dark mode, lilac accents,
Inter body text and Space Grotesk titles. Font files are bundled locally with
their SIL Open Font Licenses. Reference upload, generation settings and
experimental content motion are grouped under **Advanced**. Hover or focus
the **i** icons for input tips; reference IDs appear only in **Specific ID** mode.

Generate stylized human motion with the published Style-SALAD model on Hugging
Face ZeroGPU. This deployment runs actual inference in the Space. It does not
forward inference to the owner's Windows computer.

Choose one of the 47 released movement styles and sample a reference with a seed, choose a
specific ID from that style, or upload raw HumanML3D features `(T,263)` at 20 fps.
References need at least 41 frames and use a centered window of at most 196.
Describe an action in English. Each result provides MP4, BVH, NPY, NPZ and JSON.

Features are denormalized with the published `Comp_v6_KLD005` statistics and
reconstructed into 22 joints. MP4 is drawn from those joints over a colored
checkerboard fixed in world coordinates, with a tracking camera and trail.
BVH is a separate inverse-kinematics export from the same joints; its fitting
error is recorded in the result JSON. MP4 is not rendered from BVH.

The model is loaded at startup using ZeroGPU's CUDA emulation. Only real
sampling and reconstruction reserve GPU time. Reference download, validation,
MP4 encoding and BVH export run on CPU outside the GPU reservation. Frozen
model weights do not disable latent gradients used by style guidance.

The released 47-style catalogue is available through a small verified index.
Only the selected feature file is fetched from the official SMooDi archive
using HTTP byte ranges, with ZIP CRC and NPY validation. This repository does
not mirror datasets or pretrained weights. Generation weights and CLIP are
downloaded directly from their official public sources and verified by hash.

ZeroGPU availability and per-account daily quotas apply. Signing in to Hugging
Face can provide the account's free quota. No paid hardware or subscription
is requested by this application. Results and downloaded references use the
Space's temporary disk and can disappear on restart.

The Windows installation remains a separate alternative, with its own dataset
and results. This cloud deployment does not modify the PC's model environment.

The existing checkpoint is used without retraining. The complete 100STYLE
dataset remains preserved on the owner's D: drive; this Space exposes only the
47-style subset requested for the demonstration. Optional
DDIM content inversion is experimental and may change gestures or trajectory.

## Sources and licenses

- [Style-SALAD](https://github.com/junhyukjeon/style-salad), commit
  `4faebb83ccda8630e27fbe2189aed1928f4623a0`. Authored source is MIT; the released
  checkpoint has [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/)
  terms and is downloaded unchanged. See `upstream/LICENSE-CHECKPOINTS.md`.
- [SALAD](https://github.com/seokhyeonhong/salad) provides the backbone and
  normalization assets, downloaded from its official public release. Third-party
  terms remain applicable; see `upstream/THIRD_PARTY_NOTICES.md`.
- [CLIP](https://huggingface.co/openai/clip-vit-base-patch32), downloaded at the
  pinned official revision `3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268`.
- [100STYLE — Ian Mason](https://www.ianxmason.com/100style/), Mason, Starke and
  Komura (2022), CC BY 4.0; HumanML3D features are from the official
  [SMooDi](https://github.com/neu-vi/SMooDi) processed release.
- BVH utility attribution and the complete MoMask MIT notice are preserved in
  `adapter/THIRD_PARTY_NOTICES.md` and `adapter/_bvh/LICENSE`.
- [ZeroGPU documentation](https://huggingface.co/docs/hub/spaces-zerogpu).

No credentials are stored in this repository. Uploads are read with
`allow_pickle=False`; official checkpoints use `weights_only=True`.