apple--ml-stable-diffusion
Zach Nagengast
94dfc6b548
* Initial support for SDXL refiner * Cleanup * Add arg for converting Unet in float32 precision * Setup scale factor with pipeline in CLI * Update cli arg and future warning * Bundle refiner unet if specified * Update script for bundled refiner - Also skip loading model if check_output_correctness is missing, since the model does not require inferencing at conversion time * Flip skip_model_load bool * Cleanup * Support bundled UnetRefiner * Add seperate refiner config value - Includes unloading base unet when swapping to refiner * Update readme for SDXL refiner * Add condition for new SDXL coreml input features * Revert pipeline interface change, add extra logging on pipe load * Reset model_version after refiner conversion * Reset model_version before refiner conversion but after pipe init * Add refiner chunking * Ensure unets are unloaded for reduceMemory true * Handle missing UnetRefiner.mlmodelc on pipeline load Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Prewarm refiner on load, unload on complete * Force cpu_and_gpu for VAE until it can be fixed * Include output dtype of np.float32 for all conversions * Allow a custom VAE to be converted. * Revert hardcoded reduceMemory * Fix merge * Default chunking arg for --merge-chunks-in-pipeline-model when called from torch2coreml --------- Co-authored-by: Pedro Cuenca <pedro@huggingface.co>