Spaces:
Running on Zero
Running on Zero
| title: FrameForge | |
| emoji: 🖼️ | |
| colorFrom: purple | |
| colorTo: indigo | |
| sdk: gradio | |
| app_file: app.py | |
| pinned: false | |
| tags: | |
| - ml-intern | |
| - frameforge | |
| - image-editing | |
| - hunyuanvideo | |
| [](https://hf.co/chat?mode=ml-intern) | |
| # FrameForge — demo | |
| Unofficial interactive demo for **FrameForge: Harnessing Priors of Video Foundation | |
| Models for Unified Image Generation** ([arXiv 2610.36545](https://arxiv.org/abs/2610.36545)), | |
| built on the authors' released | |
| [inference code](https://github.com/Lyne1/FrameForge) and | |
| [official LoRA weights](https://huggingface.co/lyneeeeeeeee/FrameForge) over | |
| [HunyuanVideo 1.5](https://huggingface.co/tencent/HunyuanVideo-1.5). | |
| Three modes in one model: | |
| - **Instruction-guided editing** — "change the sky to sunset" style edits | |
| - **Subject-driven generation** — place a subject from a photo into a new scene | |
| - **Canny-to-image** — generate from an edge map (auto-extraction available) | |
| ## Running it | |
| Built for **ZeroGPU** (`xlarge` slices, 96 GB): generation functions are | |
| decorated with `@spaces.GPU`, and torch is pinned to **2.8.0** (the closest | |
| ZeroGPU-supported version to the authors' 2.6.0 pin). It also runs unchanged | |
| on a persistent GPU (A100 40 GB+ recommended; `FF_OFFLOAD=true` for smaller | |
| GPUs at a large speed cost) — the decorator is a no-op off ZeroGPU. | |
| **First run downloads ~40 GB of checkpoints.** (byt5-small/Glyph-SDXL-v2 | |
| from the authors' README are skipped — the released config sets `disable_by5=True`, | |
| so they are never loaded.) On Spaces, attach persistent | |
| storage and set `FF_CKPT_DIR=/data/ckpts` so this happens once. | |
| **Quota note:** a 50-step generation takes a few minutes of GPU time and | |
| `xlarge` consumes 2× daily quota — free accounts (5 min/day) get roughly one | |
| image per day, PRO accounts (40 min/day) get several. | |
| Required secret: `HF_TOKEN` — the pipeline pulls the **gated** | |
| [FLUX.1-Redux-dev](https://huggingface.co/black-forest-labs/FLUX.1-Redux-dev) | |
| vision encoder, so the token's account must have accepted its license. | |
| Useful env vars: `FF_CKPT_DIR` (checkpoint root), `FF_LORA_PATH`, | |
| `FF_REPO_DIR` (code cache), `FF_OFFLOAD` (`true`/`false`). | |
| ## Local run | |
| ```bash | |
| pip install -r requirements.txt | |
| python app.py | |
| ``` | |
| ## Notes | |
| - Outputs are 512×512; ~50 denoising steps on a video-model backbone, so expect | |
| a couple of minutes per image. | |
| - License: Tencent Hunyuan Community License (see the base model and the | |
| [FrameForge repo](https://github.com/Lyne1/FrameForge)) — review before | |
| redistribution or commercial use. | |
| - If you use this in research, cite the paper: https://arxiv.org/abs/2610.36545 | |