TokForge — Realistic Vision 5.1 · CoreML 6-bit (Apple Neural Engine)

A 6-bit palettized Apple CoreML conversion of Realistic Vision V5.1 (SG161222, SD-1.5 photoreal finetune), built for on-device image generation in the TokForge iOS app. Converted with Apple ml-stable-diffusion (torch2coreml) using SPLIT_EINSUM_V2 attention and --quantize-nbits 6 — 6-bit palettized weights compile fast on the Apple Neural Engine (the ANE-fast photoreal path, vs the FP16 finetunes >11-min ANE graph compile).

Part of the TokForge iOS · CoreML Image Models collection.

Files

File Size Contents
RealisticVision-5.1_palettized_split_einsum_v2_compiled.zip ~874 MB The compiled Swift-CLI resource bundle (a single ZIP of Resources/)
Resources/ ~913 MB TextEncoder.mlmodelc / Unet.mlmodelc / VAEDecoder.mlmodelc / VAEEncoder.mlmodelc + vocab.json + merges.txt

Recommended render settings (standard SD-1.5, photoreal)

attention:    split_einsum_v2 (Apple Neural Engine)
compute:      .cpuAndNeuralEngine  (palettized -> fast ANE compile)
steps:        20   (8 = fast floor, 40 = extra refinement)
cfg-scale:    7.5
resolution:   512x512  (SD-1.5 native; baked into the compiled model)

How this was built

  1. Loaded SG161222/Realistic_Vision_V5.1_noVAE (SD-1.5 diffusers; the diffusers conversion bundles a working VAE).
  2. Converted UNet + text encoder + VAE decoder + VAE encoder to CoreML with Apple ml-stable-diffusion python_coreml_stable_diffusion.torch2coreml, --attention-implementation SPLIT_EINSUM_V2.
  3. Applied 6-bit palettization (--quantize-nbits 6) for the fast iOS-17 ANE compile.
  4. Bundled the compiled resources for the Swift CLI (--bundle-resources-for-swift-cli).

Conversion peaked at ~10.9 GB RAM (no --chunk-unet needed); iOS 17+ (6-bit palettized).

License & attribution

This repository is a redistribution for on-device use — a format conversion (PyTorch -> CoreML) and 6-bit palettization of SG161222s Realistic Vision V5.1. No weights were retrained. The original OpenRAIL-M terms and attribution requirements propagate to this conversion and any images generated with it. No additional restrictions are imposed by this repackaging.

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