{ "source_model": "stable-diffusion-v1-5/stable-diffusion-v1-5", "format": "LiteRT / TFLite diffusion submodels", "image_size": [ 512, 512 ], "tokenizer_max_length": 77, "vae_scaling_factor": 0.18215, "variants": [ "fp32", "int8" ], "profiles": { "android-qnn-npu": { "platform": "android", "preferred_accelerator": "NPU", "delegate": "LiteRT Qualcomm AI Engine Direct (QNN)", "notes": [ "Mixed deployment profile for the Qualcomm NPU path through LiteRT CompiledModel.", "This notebook still exports LiteRT/TFLite submodels, not Qualcomm-specific AOT context binaries.", "Android packaging still needs Qualcomm LiteRT runtime libraries and arm64-v8a delivery." ], "source_variant": "int8", "files": { "text_encoder": "fp32/text_encoder.tflite", "unet": "int8/unet.tflite", "vae_decoder": "fp32/vae_decoder.tflite" }, "quantization": "fp32 text encoder + dynamic int8 UNet + fp32 VAE" }, "android-cpu": { "platform": "android", "preferred_accelerator": "CPU", "delegate": "LiteRT CPU/XNNPACK", "notes": [ "Conservative fallback profile for Android when GPU/NPU compilation is unavailable.", "Reuses the mixed int8 UNet path for smaller downloads and lower RAM pressure." ], "source_variant": "int8", "files": { "text_encoder": "fp32/text_encoder.tflite", "unet": "int8/unet.tflite", "vae_decoder": "fp32/vae_decoder.tflite" }, "quantization": "fp32 text encoder + dynamic int8 UNet + fp32 VAE" }, "android-gpu": { "platform": "android", "preferred_accelerator": "GPU", "delegate": "LiteRT GPU delegate", "notes": [ "Uses the float export path because LiteRT GPU delegates are the most predictable there.", "The text encoder still prefers INT32 token ids to avoid delegate-hostile INT64 input graphs." ], "source_variant": "fp32", "files": { "text_encoder": "fp32/text_encoder.tflite", "unet": "fp32/unet.tflite", "vae_decoder": "fp32/vae_decoder.tflite" }, "quantization": "fp32" }, "ios-coreml": { "platform": "ios", "preferred_accelerator": "CORE_ML", "delegate": "LiteRT Core ML delegate", "notes": [ "Core ML delegate currently supports float models, so this profile stays on the float export path.", "This notebook exports LiteRT/TFLite artifacts for the LiteRT Core ML delegate, not native `.mlmodel` files." ], "source_variant": "fp32", "files": { "text_encoder": "fp32/text_encoder.tflite", "unet": "fp32/unet.tflite", "vae_decoder": "fp32/vae_decoder.tflite" }, "quantization": "fp32", "minimum_os": "iOS 12" } }, "android_profile_priority": { "GPU": "android-gpu", "NPU": "android-qnn-npu", "CPU": "android-cpu" }, "legacy_default_variant": "int8", "preferred_text_encoder_token_dtype": "int32", "text_encoder_runtime_config": "configs/text_encoder_runtime_config.json" }