| # NumZoo LoRA — training setup (reproducible) |
|
|
| These are the exact files used to train the **NumZoo style LoRA** for FLUX.2-klein-4B |
| on [Modal](https://modal.com) using [ostris/ai-toolkit](https://github.com/ostris/ai-toolkit). |
|
|
| - **Published LoRA:** https://huggingface.co/goumsss/numzoo-flux2-klein-lora |
| - **Base model:** `black-forest-labs/FLUX.2-klein-base-4B` (train on base, infer on distilled) |
| - **Trainer:** ai-toolkit · **Compute:** Modal A100 · ~45 min · LoRA rank 32, 1500 steps |
|
|
| ## Files |
| | File | Role | |
| |------|------| |
| | `run_modal.py` | Modal app (image, GPU, volume, secret) — **rewritten for Modal ≥ 1.0** | |
| | `numzoo_klein.yaml` | ai-toolkit training config (`arch: flux2_klein_4b`, trigger, sample prompts) | |
|
|
| ## The dataset |
| The 54 training images + captions live one level up in [`../`](../) (`image_001.jpg` + |
| `image_001.txt`, …). They were generated with **Qwen-Image** (see |
| [`../../scripts/generate_dataset.py`](../../scripts/generate_dataset.py)) and captioned |
| `NUMZOO. <content>` — content only, no style words, so the trigger learns the style. |
|
|
| ## How to reproduce |
| ```bash |
| # 1. Clone ai-toolkit and drop these in |
| git clone https://github.com/ostris/ai-toolkit |
| cp run_modal.py ai-toolkit/run_modal.py |
| cp numzoo_klein.yaml ai-toolkit/config/numzoo_klein.yaml |
| cp -r <dataset> ai-toolkit/numzoo-dataset # the 54 image+txt pairs |
| |
| # 2. Modal: install, auth, and store your HF token (needs the base-model license accepted) |
| pip install modal && modal token new |
| modal secret create huggingface HF_TOKEN=hf_xxx |
| |
| # 3. Train (from inside ai-toolkit/) — checkpoints + samples land on the volume |
| cd ai-toolkit |
| modal run run_modal.py --config-file-list-str=/root/ai-toolkit/config/numzoo_klein.yaml |
| |
| # 4. Download results, pick the best checkpoint (we used step 1250) |
| modal volume get flux-lora-models numzoo_klein_lora ./lora_output |
| ``` |
|
|
| ## Gotchas we hit (so you don't) |
| - **Modal ≥ 1.0 removed `modal.Mount`** — `run_modal.py` here uses `Image.add_local_dir` |
| + `add_local_file` instead, and moves heavy imports inside the container function. |
| - **pip `resolution-too-deep`** with unpinned deps — we install from ai-toolkit's own |
| pinned `requirements.txt` (which also pins the diffusers commit that supports FLUX.2), |
| plus `torch==2.7.1`/`torchvision`/`torchaudio` first. |
| - **Gated base model** — accept the license for `FLUX.2-klein-base-4B` on HF first. |
| - **Trigger rendered as text** at inference — append `no text` to the prompt; the |
| distilled 4-step klein otherwise draws the `NUMZOO` trigger as a literal sign. |
|
|
