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license: creativeml-openrail-m |
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# Image Generation NPU Models – SD 1.5 |
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This repository contains the ONNX models and runtime libraries required to run the image generation pipeline on AMD NPUs. |
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The folder structure is organized to mirror the main components of the diffusion pipeline (UNet, VAE decoder, text encoder, tokenizer and scheduler), plus the platform-specific runtime libraries. |
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## Repository structure |
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``` |
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. |
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├─ libs/ |
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├─ scheduler/ |
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├─ text_encoder/ |
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├─ tokenizer/ |
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├─ unet/ |
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└─ vae_decoder/ |
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``` |
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### `libs/` |
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This folder contains the dynamic libraries (`.dll`) required at runtime by the NPU backend. |
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They must be placed in a location where the application can load them (e.g., in the same folder as the executable or in the system `PATH`). |
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### `unet/` |
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This folder contains the UNet model used in the diffusion process. |
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The UNet is exported and structured specifically to leverage the AMD NPU accelerator for the denoising steps. |
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### `vae_decoder/` |
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This folder contains the VAE decoder model used to map latent representations back to the image space. |
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The VAE decoder is also structured to make use of the NPU accelerator for efficient image reconstruction. |
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### `text_encoder/` |
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This folder contains the text encoder model used to convert the input prompt into conditioning embeddings for the diffusion model. |
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### `tokenizer/` |
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This folder contains the tokenizer configuration and vocabulary files required to preprocess the text prompt before it is fed to the text encoder. |
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### `scheduler/` |
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This folder contains the scheduler configuration (timesteps, betas, alphas, etc.) used during the diffusion sampling process. |
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## Release 1113 |
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This release corresponds to the **1113 build**. |
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**Included in this version:** |
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- Updated UNet and VAE Decoder models optimized for AMD NPU execution. |
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- Synchronized text encoder, tokenizer, and scheduler components aligned with the 1113 pipeline. |
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- Updated runtime DLLs in the `libs/` folder. |
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- Improved model folder structure for compatibility with Procyon and NPU execution environments. |
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**Notes:** |
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- All ONNX models in this release are validated with the 1113 test package. |
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- Ensure that the DLLs from `libs/` are correctly placed in the application’s search path. |
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- This release is intended for NPU execution; GPU versions are hosted separately. |
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## Notes |
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- UNet and VAE decoder models are optimized and structured to run on AMD NPUs. |
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- The other components (text encoder, tokenizer and scheduler) are shared between GPU and NPU pipelines, but are provided here for completeness. |
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- Please refer to the associated application or benchmark documentation for detailed integration and usage instructions (e.g., how to set model paths, environment variables and library search paths). |
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