| --- |
| license: creativeml-openrail-m |
| library_name: diffusers |
| tags: |
| - stable-diffusion |
| - sd-1.5 |
| - hyper-sd |
| - onnx |
| - text-to-image |
| - 4-step |
| base_model: emilianJR/epiCRealism |
| pipeline_tag: text-to-image |
| --- |
| |
| # epiCRealism + Hyper-SD (4-step) — ONNX |
|
|
| ONNX export of [emilianJR/epiCRealism](https://huggingface.co/emilianJR/epiCRealism) with the [ByteDance/Hyper-SD](https://huggingface.co/ByteDance/Hyper-SD) 4-step LoRA fused into the UNet. SD 1.5 architecture, 512×512 native, Euler scheduler, CFG = 1, **4 steps**. |
|
|
| epiCRealism leans heavily toward photorealistic environments and natural lighting. Pick this one over Realistic Vision when the subject is "a place" rather than "a person." |
|
|
| Converted artifact, not a new model. Training credit: emilianJR (epiCRealism), ByteDance (Hyper-SD). |
|
|
| ## What this repo contains |
|
|
| ``` |
| model_index.json |
| feature_extractor/ |
| scheduler/ |
| text_encoder/ |
| tokenizer/ |
| unet/ # epiCRealism UNet + Hyper-SD-15 4-step LoRA fused in |
| vae_decoder/ |
| vae_encoder/ |
| ``` |
|
|
| ## How it was produced |
|
|
| 1. Load `emilianJR/epiCRealism` via `diffusers`. |
| 2. Load `ByteDance/Hyper-SD/Hyper-SD15-4steps-lora.safetensors` via `peft`, `fuse_lora()` into UNet. |
| 3. Save fused pipeline; run `optimum-cli export onnx`. |
|
|
| Toolchain: `optimum 1.24.0`, `diffusers 0.31.0`, `transformers 4.45.2`, `torch 2.4.x` (CUDA 12.4). Conversion script: [`scripts/export-epicrealism-hyper.ps1`](https://github.com/HeliosophLLC/DatumIngest/blob/main/scripts/export-epicrealism-hyper.ps1). |
|
|
| ## Inference notes |
|
|
| | Setting | Value | |
| |---|---| |
| | Scheduler | Euler | |
| | Steps | 4 | |
| | CFG / guidance scale | 1.0 | |
| | Negative prompt | Skip | |
| | Resolution | 512×512 native | |
|
|
| ## License |
|
|
| CreativeML OpenRAIL-M, inherited from SD 1.5 + epiCRealism + Hyper-SD. License files included. By using this model you accept those terms. |
|
|
