| --- |
| license: cc-by-nc-4.0 |
| library_name: onnxruntime |
| pipeline_tag: text-to-image |
| base_model: carlofkl/DreamLite-mobile |
| tags: |
| - dreamlite |
| - onnx |
| - android |
| - experimental |
| --- |
| |
| # DreamLite Android — one model, 512 / 1024 px |
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| Experimental ONNX conversion of [DreamLite-mobile](https://huggingface.co/carlofkl/DreamLite-mobile/tree/diffusers), for the independent DreamLite Lab Android test application. Original implementation: [ByteVisionLab/DreamLite](https://github.com/ByteVisionLab/DreamLite). |
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| ## Files |
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| Download the **single `shared/` package** (~1.57 GB total). `dreamlite_weights.bin` holds one exact shared copy of the large weights. Four small ONNX execution graphs select UNet/decoder and 512/1024 tensor shapes. Keep all five files in the same directory without renaming. Sizes and SHA-256 hashes are listed in `shared/manifest.json`. |
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| APK 0.3 defaults to 512px / 1 step and allows 512/1024 and 1/2/4-step selection in Settings. Download once; changing resolution or step count does not download another weight set. 1024px inference is native generation, not upscaling a 512px result. These are static-shape FP32 ONNX opset-17 graphs sharing weights, not a single dynamic-shape ONNX graph. |
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| Older standalone `512/` and `1024/` packages were replaced on the main branch; pinned commits remain available for older test APKs. |
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| The application defaults to **512 × 512, 1 step** and offers 2/4-step comparison. One-step output is experimental and visibly softer in the local sample; four steps is the quality reference. This is not a model trained specifically for one-step inference. |
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| ## Scope and validation |
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| - Fixed, pre-encoded text condition in the test APK: a red ceramic teapot on a wooden table near a window, seed 42. The output image is generated on each run, not cached. |
| - The 2B text/image encoder is **not** included. This package does not provide arbitrary text entry or photo editing in the test APK. |
| - CPU ONNX numerical checks and a complete 512px, one-step image comparison against the PyTorch baseline were performed. This does not establish general image quality or mobile speed. |
| - Complete 1024px, four-step CPU output comparison passed the preset image threshold (PSNR 75.57 dB, pixel MAE 0.001803 on a 0–255 scale). The 1024 UNet's stricter elementwise tolerance test failed (maximum absolute error 0.003335); this record is retained. One/two-step 1024 quality has not been separately evaluated. These remain experimental test models. |
| - QNN HTP strict mode requests FP16 execution and disables CPU fallback. **DreamLite phone NPU compatibility and sub-second latency remain unverified.** These are not the paper's W8A8 quantized weights. |
| - This 512px experiment does not demonstrate the 1024px, multi-condition project target. |
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| ## Provenance and license |
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| Original checkpoint revision: `6695c3f4be230f0493fa5dbf78be3bc4d3bb2ab4` (`diffusers` branch). |
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| The upstream model card specifies CC BY-NC 4.0. The original weight license is included as `LICENSE`; original authors retain their rights. This repository contains derived conversions, not an official release. Use is for non-commercial research. The uploader has confirmed permission from the author to publicly host these converted weights; no additional commercial rights are granted here. Consult the original authors for other uses and follow their ethical restrictions. |
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