Add ComfyUI-ready LoRA, examples, converter, README, LICENSE

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LICENSE

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README.md

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+---
+license: apache-2.0
+base_model:
+  - Tongyi-MAI/Z-Image
+  - Tongyi-MAI/Z-Image-Turbo
+base_model_relation: adapter
+pipeline_tag: text-to-image
+library_name: diffusers
+tags:
+  - lora
+  - text-to-image
+  - z-image
+  - comfyui
+  - realism
+---
+
+# RealGen-V2 — ComfyUI-ready LoRA for Z-Image
+
+A drop-in [ComfyUI](https://github.com/comfyanonymous/ComfyUI) build of
+[Yunncheng/RealGen-V2](https://huggingface.co/Yunncheng/RealGen-V2). Same
+weights as upstream, repackaged so ComfyUI's stock `LoraLoader` can load it
+without a custom node. Works on both Z-Image base and Z-Image-Turbo.
+
+## Examples
+
+Each row is the **same prompt and seed**, rendered with and without the LoRA
+at strength `1.0`.
+
+### [Z-Image (base)](https://huggingface.co/Tongyi-MAI/Z-Image)
+
+| Without LoRA | With RealGen-V2 |
+| --- | --- |
+| ![Z-Image base, prompt 1, no LoRA](examples/base/z-image-regular_00001_.jpg) | ![Z-Image base, prompt 1, with RealGen-V2](examples/base/z-image-realgen_00001_.jpg) |
+| ![Z-Image base, prompt 2, no LoRA](examples/base/z-image-regular_00002_.jpg) | ![Z-Image base, prompt 2, with RealGen-V2](examples/base/z-image-realgen_00002_.jpg) |
+| ![Z-Image base, prompt 3, no LoRA](examples/base/z-image-regular_00003_.jpg) | ![Z-Image base, prompt 3, with RealGen-V2](examples/base/z-image-realgen_00003_.jpg) |
+| ![Z-Image base, prompt 4, no LoRA](examples/base/z-image-regular_00004_.jpg) | ![Z-Image base, prompt 4, with RealGen-V2](examples/base/z-image-realgen_00004_.jpg) |
+| ![Z-Image base, prompt 5, no LoRA](examples/base/z-image-regular_00005_.jpg) | ![Z-Image base, prompt 5, with RealGen-V2](examples/base/z-image-realgen_00005_.jpg) |
+
+### [Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)
+
+| Without LoRA | With RealGen-V2 |
+| --- | --- |
+| ![Z-Image-Turbo, prompt 1, no LoRA](examples/turbo/z-image-turbo-regular_00001_.jpg) | ![Z-Image-Turbo, prompt 1, with RealGen-V2](examples/turbo/z-image-turbo-realgen_00001_.jpg) |
+| ![Z-Image-Turbo, prompt 2, no LoRA](examples/turbo/z-image-turbo-regular_00002_.jpg) | ![Z-Image-Turbo, prompt 2, with RealGen-V2](examples/turbo/z-image-turbo-realgen_00002_.jpg) |
+| ![Z-Image-Turbo, prompt 3, no LoRA](examples/turbo/z-image-turbo-regular_00003_.jpg) | ![Z-Image-Turbo, prompt 3, with RealGen-V2](examples/turbo/z-image-turbo-realgen_00003_.jpg) |
+| ![Z-Image-Turbo, prompt 4, no LoRA](examples/turbo/z-image-turbo-regular_00004_.jpg) | ![Z-Image-Turbo, prompt 4, with RealGen-V2](examples/turbo/z-image-turbo-realgen_00004_.jpg) |
+| ![Z-Image-Turbo, prompt 5, no LoRA](examples/turbo/z-image-turbo-regular_00005_.jpg) | ![Z-Image-Turbo, prompt 5, with RealGen-V2](examples/turbo/z-image-turbo-realgen_00005_.jpg) |
+
+Note: on Turbo the LoRA still affects the image even though negative prompts
+don't — CFG=1 disables the negative branch, not the LoRA patch.
+
+## Why this repo exists
+
+The upstream release ships the adapter in [PEFT](https://github.com/huggingface/peft)
+format (`base_model.model.<path>.lora_A.<adapter>.weight` keys, with
+`lora_alpha` living separately in `adapter_config.json`). ComfyUI's stock
+`LoraLoader` doesn't understand that layout, so this repo provides:
+
+- the **same weights, repackaged** with diffusers-style keys
+  (`<path>.lora_down.weight`, `<path>.lora_up.weight`) and
+- per-module `alpha` tensors baked into the file so the `alpha/rank` scaling
+  ComfyUI applies matches what PEFT would have applied at runtime.
+
+No retraining, no quantisation, no surgery beyond key renaming and alpha
+injection — the math is identical to running the original adapter through PEFT.
+
+## Files
+
+| File | Purpose |
+| --- | --- |
+| `realgen_v2.safetensors` | The repackaged LoRA. Drop into `ComfyUI/models/loras/`. |
+| `scripts/convert_realgen_v2.py` | The script used to produce it from the upstream PEFT adapter. Re-runnable for transparency. |
+| `examples/` | Side-by-side renders, with and without the LoRA, on both Z-Image base and Z-Image-Turbo. |
+| `LICENSE` | Apache 2.0 (matches both RealGen-V2 and Z-Image upstream). |
+
+## Usage in ComfyUI
+
+1. Download `realgen_v2.safetensors` and place it in `ComfyUI/models/loras/`.
+2. Build a graph: `Load Diffusion Model` (Z-Image) → `LoraLoader` → sampler.
+   - Select `realgen_v2.safetensors` in the loader.
+   - **Strength `1.0`** reproduces the upstream training intent
+     (`alpha=128, rank=64 → scale=2.0`).
+   - Lower (e.g. `0.5–0.8`) for a softer effect; the LoRA scales linearly.
+
+That's it — there is no custom node to install.
+
+## Reproducing the conversion
+
+If you'd rather convert the upstream weights yourself:
+
+```bash
+# from a Python env with torch + safetensors + packaging:
+python scripts/convert_realgen_v2.py adapter_model.safetensors realgen_v2.safetensors
+```
+
+The script reads `lora_alpha` from `adapter_config.json` (sitting next to the
+adapter), strips the `base_model.model.` prefix, rewrites
+`lora_A`/`lora_B` → `lora_down`/`lora_up`, and writes one `<module>.alpha`
+tensor per LoRA module. See the source for the full mapping.
+
+## Credits
+
+- Original RealGen-V2 weights: [Yunncheng/RealGen-V2](https://huggingface.co/Yunncheng/RealGen-V2)
+- RealGen training code: [yejy53/RealGen](https://github.com/yejy53/RealGen) (`RealGen_v2/`)
+- Base models: [Tongyi-MAI/Z-Image](https://huggingface.co/Tongyi-MAI/Z-Image) and [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)
+
+This repo redistributes the weights under their original Apache 2.0 license;
+all credit for the LoRA itself belongs to the upstream authors.

realgen_v2.safetensors

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+oid sha256:c50a3437f85592512f92a2f956d699c6fc524e2b05cc77a05dc47a3057133973
+size 317598656

scripts/convert_realgen_v2.py

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+"""
+Convert the RealGen-V2 PEFT LoRA adapter into a ComfyUI-compatible LoRA.
+
+Input:  adapter_model.safetensors  (+ adapter_config.json in the same folder,
+        used to read `lora_alpha` so ComfyUI scales the LoRA correctly)
+Output: a single safetensors file with diffusers-style keys
+        (`<path>.lora_down.weight`, `<path>.lora_up.weight`, `<path>.alpha`).
+
+Drop the output file into `ComfyUI/models/loras/` and load it with the stock
+`LoraLoader` against a Z-Image model.
+
+Usage:
+  python convert_realgen_v2.py adapter_model.safetensors realgen_v2.safetensors
+  python convert_realgen_v2.py adapter_model.safetensors            # auto-names
+  python convert_realgen_v2.py                                      # cwd defaults
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+import torch
+import safetensors.torch as st
+
+
+PEFT_PREFIX = "base_model.model."
+SUFFIX_MAP = (("lora_A", "lora_down"), ("lora_B", "lora_up"))
+
+
+def convert(src: Path, dst: Path, alpha_override: float | None = None) -> None:
+    if not src.is_file():
+        sys.exit(f"error: source not found: {src}")
+
+    # Pull lora_alpha from adapter_config.json if present, else fall back.
+    lora_alpha: float
+    if alpha_override is not None:
+        lora_alpha = float(alpha_override)
+        print(f"using alpha override: {lora_alpha}")
+    else:
+        cfg_path = src.parent / "adapter_config.json"
+        if cfg_path.is_file():
+            with cfg_path.open() as f:
+                cfg = json.load(f)
+            lora_alpha = float(cfg.get("lora_alpha", 1.0))
+            print(f"read lora_alpha={lora_alpha} from {cfg_path.name}")
+        else:
+            lora_alpha = 128.0  # documented default for RealGen-V2
+            print(
+                f"warning: no adapter_config.json next to {src.name}; "
+                f"falling back to lora_alpha={lora_alpha}"
+            )
+
+    sd = st.load_file(str(src))
+    out: dict[str, torch.Tensor] = {}
+    modules: set[str] = set()
+    skipped: list[str] = []
+
+    for k, v in sd.items():
+        nk = k
+        if nk.startswith(PEFT_PREFIX):
+            nk = nk[len(PEFT_PREFIX):]
+
+        rewritten = False
+        for peft_part, comfy_part in SUFFIX_MAP:
+            tag = f".{peft_part}."
+            if tag in nk and nk.endswith(".weight"):
+                head, _ = nk.split(tag, 1)
+                nk = f"{head}.{comfy_part}.weight"
+                modules.add(head)
+                rewritten = True
+                break
+
+        if not rewritten and not nk.endswith(".alpha"):
+            skipped.append(k)
+            continue
+
+        out[nk] = v.contiguous()
+
+    if not modules:
+        sys.exit(
+            "error: no LoRA tensors detected. "
+            "Is this actually a PEFT adapter_model.safetensors?"
+        )
+
+    # Inject per-module alpha tensors if the source didn't ship them.
+    alpha_tensor = torch.tensor(lora_alpha, dtype=torch.float32)
+    for m in modules:
+        out.setdefault(f"{m}.alpha", alpha_tensor.clone())
+
+    dst.parent.mkdir(parents=True, exist_ok=True)
+    st.save_file(out, str(dst))
+
+    print(f"wrote {dst}")
+    print(f"  tensors: {len(out)}  (modules: {len(modules)})")
+    if skipped:
+        print(f"  skipped {len(skipped)} unrecognized keys, e.g. {skipped[:3]}")
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser(description=__doc__.splitlines()[1])
+    ap.add_argument(
+        "src",
+        nargs="?",
+        default="adapter_model.safetensors",
+        type=Path,
+        help="Input PEFT adapter (default: ./adapter_model.safetensors)",
+    )
+    ap.add_argument(
+        "dst",
+        nargs="?",
+        default=None,
+        type=Path,
+        help="Output filename (default: <src stem>_comfy.safetensors)",
+    )
+    ap.add_argument(
+        "--alpha",
+        type=float,
+        default=None,
+        help="Override lora_alpha instead of reading adapter_config.json.",
+    )
+    args = ap.parse_args()
+
+    src: Path = args.src
+    dst: Path = args.dst or src.with_name(f"{src.stem}_comfy.safetensors")
+    convert(src, dst, alpha_override=args.alpha)
+
+
+if __name__ == "__main__":
+    main()