Modelpublic

ladparis/Z-Image-Turbo-LiteRT-iOS

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face

0likes91downloads

Model Card

Z-Image-Turbo — LiteRT bundle for Mirage iOS

Repackaged from litert-community/Z-Image-Turbo-LiteRT (Apache-2.0, converted from 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).