---
license: mit
tags: [text-to-image, latent-consistency-model, coreml, onnx]
base_model: SimianLuo/LCM_Dreamshaper_v7
---

# CV Studio illustrator (on-device)

Ready-to-run conversions used by the CV Studio desktop app to draw one illustration per sentence of a video, on the
customer's own machine (no PyTorch at run time):

| Folder | Runtime | Contents |
|---|---|---|
| `macos/` | Core ML (macOS 14+, Apple Silicon) | `text_encoder.mlpackage` (fp16), `unet_6bit.mlpackage` (6-bit palettised), `taesd_decoder.mlpackage`, `tokenizer.json` |
| `windows/` | ONNX Runtime (CPU / DirectML) | `text_encoder_int8.onnx`, `unet_int8.onnx` (dynamic int8), `taesd_decoder.onnx`, `tokenizer.json` |

Inputs: UNet `(sample 1×4×64×64, timestep 1, encoder_hidden_states 1×77×768) → noise_pred`, with the LCM guidance
embedding (w = 8) built in; 4 LCM steps; the TAESD decoder returns RGB in [0, 1] at 512×512. `manifest.json` lists
every file with its size and SHA-256.

## Origin and licences

- **LCM_Dreamshaper_v7** by Simian Luo et al. (https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7), published under
  the **MIT** licence; it is a latent consistency model distilled from **DreamShaper v7** (Lykon), a Stable Diffusion
  1.5 fine-tune released under the **CreativeML OpenRAIL-M** licence. To respect the upstream terms, the use
  restrictions of OpenRAIL-M (Attachment A: no illegal, harmful, discriminatory, defamatory or deceptive use, no
  medical advice, no exploitation of minors, etc.) are passed on to users of these files.
- **TAESD** (Tiny AutoEncoder for Stable Diffusion) by Ollin Boer Bohan (https://github.com/madebyollin/taesd), MIT.
- The conversions (Core ML palettisation, ONNX export and int8 quantisation) were made by the CV Studio team; no
  weights were retrained.