just run the same command again. It will print `#### IMPORTANT RESUMING FROM step XXXX ####` and continue from there. For a 7-hour run this is essential — checkpoints save every 250 steps as configured in `save_every`.

**Resolution tradeoff:** SDXL trained without issue at [512, 1024]. Flux cannot — the 1024 bucket (832×1216 / 1216×832) OOMs during the forward/backward pass even with uint4, because weights are dequantized to bf16 at compute time. Training at [512, 768] means the LoRA sees a maximum of 768px. Flux can still generate at 1024px or higher at inference time — the LoRA extrapolates. For portrait and social media use (viewed on phones at 1080px or less), the quality difference is negligible compared to the alternative of skipping ~30% of training batches due to OOM.

---

## ComfyUI Flux Setup

After training, you need to point ComfyUI at your Flux models. The HuggingFace download already has everything — just symlink rather than copy.

### Model symlinks

ComfyUI expects models in specific subdirectories under `~/ComfyUI/models/`. Create symlinks from those locations into `~/models/flux/`:

```bash
# Flux transformer (single-file, 23GB)
ln -s ~/models/flux/flux1-dev.safetensors ~/ComfyUI/models/diffusion_models/flux1-dev.safetensors

# VAE
ln -s ~/models/flux/ae.safetensors ~/ComfyUI/models/vae/ae.safetensors

# CLIP text encoder
ln -s ~/models/flux/text_encoder/model.safetensors ~/ComfyUI/models/clip/clip_l.safetensors
```

### T5 text encoder: merging shards

The HuggingFace Flux download stores T5 sharded across two files (`model-00001-of-00002.safetensors` and `model-00002-of-00002.safetensors` in `text_encoder_2/`). ComfyUI needs a single file. The merge is straightforward — the shards are the same format, just split by size, with no key remapping needed:

```python
import os
from safetensors.torch import load_file, save_file

home = os.path.expanduser("~")
shard1 = load_file(f"{home}/models/flux/text_encoder_2/model-00001-of-00002.safetensors")
shard2 = load_file(f"{home}/models/flux/text_encoder_2/model-00002-of-00002.safetensors")
merged = {**shard1, **shard2}
save_file(merged, f"{home}/ComfyUI/models/clip/t5xxl_fp16_merged.safetensors")
```

Result: 219 tensors, 9.5GB, keys in standard T5 format (`encoder.block.0.layer.0.SelfAttention.k.weight`). No key conflicts. Original shards are untouched — to revert: `rm ~/ComfyUI/models/clip/t5xxl_fp16_merged.safetensors`.

Alternative if you prefer not to merge: download the standalone `t5xxl_fp8_e4m3fn.safetensors` (~4.9GB, fp8 precision) from HuggingFace and place it in `~/ComfyUI/models/clip/`. Adjust the workflow to point to that filename.

### Workflow JSON

Flux uses a different node set from SDXL in ComfyUI. SDXL uses `CheckpointLoaderSimple` which loads everything from one file. Flux loads each component separately because the sources are separate files. The native node graph:

- **UNETLoader** → loads `flux1-dev.safetensors` (stored in bf16; ComfyUI quantizes to fp8_e4m3fn on load)
- **DualCLIPLoader** → loads `clip_l.safetensors` + `t5xxl_fp16_merged.safetensors`
- **VAELoader** → loads `ae.safetensors`
- **LoraLoader** → applies the trained LoRA to model and CLIP
- **CLIPTextEncode** → encodes the positive prompt
- **EmptyLatentImage** → creates the starting latent (1024×1024)
- **RandomNoise** → generates noise seed
- **BasicGuider** → combines model + conditioning (replaces CFGGuider for Flux)
- **KSamplerSelect** → selects sampler algorithm (euler)
- **BasicScheduler** → generates sigma schedule (simple, 25 steps)
- **SamplerCustomAdvanced** → runs the full sampling loop
- **VAEDecode** → latent → pixel image
- **SaveImage** → saves to `~/ComfyUI/output/`

No custom nodes required. The node graph above is the complete workflow.

After training completes, symlink the LoRA output (replace `[your-lora-name]` with the `name` from your training config):
```bash
ln -sf ~/ai-toolkit-amd-rocm-support/output/[your-lora-name]/[your-lora-name]_000001500.safetensors \
~/ComfyUI/models/loras/flux_portrait_lora.safetensors
```

(`-sf` forces the symlink

update — useful if you tested with an earlier checkpoint and are now pointing at the final one.)

### Generation speed

Flux is noticeably slower than SDXL in ComfyUI — 25 steps takes considerably longer due to the 23GB transformer size and fp8 dequantization at inference time.

---

## Face Restoration in ComfyUI

**Do not use ReActor on ROCm.** ReActor (`Gourieff/ComfyUI-ReActor`) uses ONNX Runtime for InsightFace face detection. The ROCm Execution Provider was removed from ORT 1.23 — on ROCm 7.1+ only the CPU EP is available via pip, so face detection runs on CPU.

**Use `facerestore_cf` instead** (https://github.com/mav-rik/facerestore_cf) — pure PyTorch, no ONNX Runtime, runs fully on GPU on ROCm.

### Install

```bash
cd ~/ComfyUI/custom_nodes
git clone https://github.com/mav-rik/facerestore_cf
source ~/ComfyUI/venv/bin/activate
pip install -r facerestore_cf/requirements.txt
```

**Watch out for `basicsr`** — an older package that breaks with modern PyTorch. If you get import errors after install: `pip uninstall basicsr`.

Restart ComfyUI to load the new nodes.

### Models

Download into `~/ComfyUI/models/facerestore_models/`:

```bash
# CodeFormer — better identity preservation, recommended for portraits (~359MB)
wget -P ~/ComfyUI/models/facerestore_models/ \
https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth

# GFPGAN v1.4 — faster, better for skin texture
wget -P ~/ComfyUI/models/facerestore_models/ \
https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth
```

Face detection models (RetinaFace) auto-download on first run.

### Workflow wiring

Place **after VAEDecode, before SaveImage**:

```
[sampler] → VAEDecode → FaceRestoreWithModel → SaveImage
```

For Flux the sampler node is `SamplerCustomAdvanced`; for SDXL it is `KSampler`.

---

## Summary: What Actually Works on RX 9060 XT (gfx1200) as of May 2026

| Task | Works? | Notes |
|------|--------|-------|
| ROCm 7.2.3 install | ✓ | Via amdgpu-install; manually add user to render/video groups |
| PyTorch 2.11.0+rocm7.2 | ✓ | Stable index only; nightly crashes |
| bitsandbytes (compiled) | ✓ | Must build from source with -DBNB_ROCM_ARCH=gfx1200 |
| JoyCaption captioning | ✓ | 3 bugs to fix (documented above); 5 sec/photo, 11.7GB VRAM |
| SDXL LoRA training | ✓ | 1500 steps in 76 min; 10GB VRAM peak; bf16 required |
| SDXL ComfyUI generation | ✓ | HSA_OVERRIDE_GFX_VERSION=12.0.0 required; dpmpp_2m karras, CFG 7.0 |
| Flux.1 Dev training (uint4) | ✓ | 5 code patches + cache_text_embeddings + num_workers: 0 + [512, 768] required; zero OOM skips confirmed; qint4 fails (CUDA-only) |
| Flux ComfyUI generation | ✓ | Symlinks + T5 shard merge confirmed working; slower than SDXL (expected) |
| Flux LoRA 1500-step training | ✓ | Completed — ~7 hours, 13.7–14.4GB VRAM, final loss 0.369, ~15 sec/step |
| WSL2 training | ✗ | DXG bridge bug (libthunk_proxy.a), unfixed as of May 2026 |

https://redd.it/1tgggrv
@rStableDiffusion

LTX 2.3 Get a interesting sound!

https://redd.it/1tghcfz
@rStableDiffusion

Lance by ByteDance: 3B Apache2 model for image and video understanding, generation, and editing
https://redd.it/1tgjrm2
@rStableDiffusion

i need this hairstyle as prompts , no AI has managed to do it , they always give me a different hair , thanks in advance
https://redd.it/1tgk08w
@rStableDiffusion

Two staged workflow: ZIB to ZIT
https://redd.it/1tgkoag
@rStableDiffusion

The video is always like this.Why?

https://redd.it/1tgnk7w
@rStableDiffusion

Feels like AI chatbot tools in 2026 are becoming part of creative workflows now

Kinda crazy how many Stable Diffusion workflows now include some AI chatbot alongside image generation.
People are using them for prompt refinement, scene ideas, even full workflow planning.
Feels less like separate tools now and more like one combined creative setup.
Curious what everyone here is pairing with SD lately.

https://redd.it/1tgq0ua
@rStableDiffusion

ARCHIVE.REDACTED // CASE_015 — THE CUSTODIAN RADIO
https://redd.it/1tgs6th
@rStableDiffusion

Created a workflow to clone any fashion video

https://redd.it/1tgvbwo
@rStableDiffusion

are these models outdated?
https://redd.it/1tgqzkm
@rStableDiffusion

How to use LTX Director - A Free Tool for Creating Advanced LTX 2.3 Videos in ComfyUI
https://youtu.be/vM60pJJqqEI

https://redd.it/1tgyrsa
@rStableDiffusion

Trying to distill the soon-to-be-sunset Imagen 4 to a LoRA for Illustrious 2.0 but the result is a bit wonky, would appreciate some pointers

https://redd.it/1th114r
@rStableDiffusion