---
license: openrail++
tags:
  - stable-diffusion-xl
  - realvisxl
  - lightning
  - qualcomm
  - hexagon
  - qnn
  - npu
  - text-to-image
  - tokforge
library_name: qnn
pipeline_tag: text-to-image
inference: false
---

## TokForge

- **Website:** https://tokforge.ai
- **Discord:** https://discord.gg/Acv3CBtfVm
- **Google Play:** https://play.google.com/store/apps/details?id=dev.tokforge
- **iOS TestFlight:** https://testflight.apple.com/join/jnufjzRr

Runs on-device in the TokForge app.

# TokForge — RealVisXL V4.0 Lightning (Qualcomm Hexagon NPU)

**RealVisXL V4.0 Lightning** image generation for the **Qualcomm Hexagon NPU (HTP)**, packaged for
**on-device** image generation in the **TokForge** Android app (`dev.tokforge`). This is the
higher-quality **1024×1024** "Faithful" tier alongside the SD1.5 NPU bundle.

vc410: this repo replaces the previous **SDXL-Turbo** bins (few-step distillation gave fused heads /
doubled bodies / extra limbs) with **RealVisXL V4.0 Lightning**, which is adversarially distilled for
**deterministic few-step Euler** and renders clean, photoreal people. The W8A16 NPU quant is
unchanged — the checkpoint was the cure.

The model is quantized to **W8A16** (8-bit weights, 16-bit activations) and compiled to **QNN HTP
context binaries** that run on the phone's Hexagon DSP. The pipeline uses **fp16 text encoders** and a
**TAESDXL** tiny-VAE decoder, runs **6-step EulerDiscrete**, and is **guidance-free** (one UNet pass
per step).

## Based on

[`SG161222/RealVisXL_V4.0_Lightning`](https://huggingface.co/SG161222/RealVisXL_V4.0_Lightning) —
CreativeML OpenRAIL++-M license (commercial use permitted, no revenue cap).

## Format

**QNN HTP context binaries** (W8A16), native **1024px** (128×128 latent). These are compiled for the
Hexagon DSP and are **not** a portable format like GGUF. The repo ships **native sets for V73 / V75 /
V79 / V81**; the app reads the device Hexagon arch (`dsp_arch`) and downloads the matching set.
Forward-compatibility (a lower-arch binary also runs on a higher-arch DSP) still applies as a
fallback. Device-verified clean on **V75** (Lenovo SM8650) and **V81** (RedMagic SM8850).

## Pipeline

| Stage | File |
|-------|------|
| CLIP-L text encoder (fp16) | `<arch>/text_encoder_1_fp16.bin` |
| OpenCLIP-bigG text encoder (fp16) | `<arch>/text_encoder_2_fp16.bin` |
| Combined-emb MLP (host CPU) | `<arch>/sdxl_emb_mlp.bin` |
| UNet (W8A16, DSP) | `<arch>/unet.bin` |
| TAESDXL tiny-VAE (CPU MNN) | `<arch>/taesdxl_decoder.mnn` |
| Dual CLIP BPE tokenizers | `<arch>/tokenizer/`, `<arch>/tokenizer_2/` |

Scheduler: **EulerDiscrete** (deterministic), trailing spacing, epsilon prediction, **6 steps**,
guidance_scale 0. Runs via the license-clean `libsdxl_qnn_driver` in the TokForge app.

See `manifest.json` for the per-arch file list, sizes, and md5 checksums.

## Reference-image (IP-Adapter / identity-preserving) — `ip/` subfolder

The `ip/` subfolder ships the **IP-Adapter context bins** for identity-preserving
(reference-image) rendering. When a reference photo is attached, the driver swaps the base
`unet.bin` for the **IP-baked UNet** (`unet_ip.bin`) and renders **with** the reference's identity;
no-reference renders are unchanged.

| File | What |
|------|------|
| `ip/v75/unet_ip.bin` | IP-Adapter UNet context bin, Hexagon **V75** (device-verified) |
| `ip/v81/unet_ip.bin` | IP-Adapter UNet context bin, Hexagon **V81** (compiled from the same DLC; on-device validation pending) |
| `ip/model_w8a16.dlc` | arch-agnostic W8A16 QAIRT 2.40 DLC the per-arch `unet_ip.bin` are compiled from |
| `ip/ip_kv_proj_weights.npz` | 70× `to_k_ip`/`to_v_ip` Linear weights for the CPU IP side (`k_0..k_69`, `v_0..v_69`, `inner[70]`, `heads[70]`) |

The bins are **identity-agnostic** and safe to publish: the 70 cross-attention `k_ip`/`v_ip` are
**render-constant** inputs computed on the **CPU per render** (reference → CLIP-ViT-H penultimate →
plus-face Resampler → 70× `to_k_ip`/`to_v_ip`), so no likeness is baked into the published files.
The CLIP-ViT-H encoder + plus-face adapter weights are the standard public
[h94/IP-Adapter](https://huggingface.co/h94/IP-Adapter) SDXL plus-face files and are not re-hosted
here. The app downloads `unet_ip.bin` as an **optional** bundle file (paired in each set's `files`
map); its absence degrades to a plain (no-identity) render and never fails the install. IO contract,
checksums, and per-arch details are in `manifest.json` under the top-level `ip` block.