| --- |
| license: apache-2.0 |
| base_model: Tongyi-MAI/Z-Image-Turbo |
| tags: |
| - litert |
| - tflite |
| - text-to-image |
| - on-device |
| - diffusion-transformer |
| - int8 |
| pipeline_tag: text-to-image |
| library_name: litert |
| --- |
| |
| # Z-Image-Turbo — LiteRT bundle for Mirage iOS |
|
|
| Repackaged from [litert-community/Z-Image-Turbo-LiteRT](https://huggingface.co/litert-community/Z-Image-Turbo-LiteRT) |
| (Apache-2.0, converted from [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)) |
| with the host-side tensors required to run the full text-to-image pipeline on device: |
|
|
| | File | Role | |
| |---|---| |
| | `qwen_enc.tflite` | Qwen3-4B text encoder (penultimate hidden state) | |
| | `z_embx.tflite` / `z_refx.tflite` | image patch embed + noise refiner | |
| | `z_embc.tflite` / `z_refc.tflite` | caption embed + context refiner | |
| | `zc_main0..5.tflite` | 30 S3-DiT layers, 5 per chunk | |
| | `zc_final.tflite` | final adaLN + projection | |
| | `zvae.tflite` | VAE decoder | |
| | `host_tensors.safetensors` | `embed_tokens` (fp32), `t_embedder` MLP, `cap_pad_token`, `x_pad_token` | |
| | `tokenizer.json` | Qwen2 BPE tokenizer | |
|
|
| All graphs are INTEGER-int8, fixed 256×256 output, 64-token prompt budget. |
| The host loop (RoPE, adaLN timestep embedding, pad masking, x/cap concat, |
| flow-match Euler, VAE denorm `latents / 0.3611 + 0.1159`) runs in app code. |
|
|
| License: Apache-2.0 (inherited from Z-Image-Turbo). |
|
|
