Heliosoph/dreamshaper-cfg-onnx
DreamShaper 8 (CFG, full quality) — ONNX
ONNX export of Lykon/dreamshaper-8 (which ships its own VAE). No distillation LoRA — this is the full, non-distilled UNet driven with classifier-free guidance. SD 1.5 architecture, 512×512 native, Euler scheduler, CFG ≈ 7.5, ~25 steps.
This is the quality counterpart to the 4-step Hyper export. The Hyper variant is distilled for fast, CFG-free, 1–4 step sampling; it's great for previews and batch work but caps fidelity and prompt adherence. This non-distilled export, run with classifier-free guidance, a negative prompt, and a normal step budget, recovers the sharp, prompt-faithful, richly detailed output DreamShaper is known for — at a higher per-image cost (the UNet runs twice per step, over ~25 steps).
DreamShaper 8 is one of the most popular stylized SD 1.5 fine-tunes — fantasy, concept art, painterly and illustrative looks. It responds strongly to art-direction keywords (concept art, digital painting, intricate detail).
Converted artifact. Training credit: Lykon (DreamShaper).
What this repo contains
model_index.json
feature_extractor/
scheduler/
text_encoder/
tokenizer/
unet/ # DreamShaper 8 UNet, non-distilled (no LoRA)
vae_decoder/ # DreamShaper 8 bundled VAE
vae_encoder/How it was produced
- Load
Lykon/dreamshaper-8viadiffusers(uses its bundled VAE). optimum-cli export onnx(no LoRA fusion step).
Exported at FP32 — the SD 1.5 VAE is fp16-fragile (it overflows and posterizes), so the quality export stays full precision.
Toolchain: optimum 1.24.0, diffusers 0.31.0, transformers 4.45.2, torch 2.4.x (CUDA 12.4). Conversion script: `scripts/export-dreamshaper-cfg.ps1`.
Inference notes
Classifier-free guidance runs the UNet twice per step (conditional + unconditional) and combines them as uncond + guidance · (cond − uncond). The negative prompt only takes effect when guidance > 1.
License
CreativeML OpenRAIL-M (SD 1.5 + DreamShaper). License files included. By using this model you accept those terms.
