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metadata
license: creativeml-openrail-m
tags:
  - text-to-image
  - stable-diffusion
  - realistic-vision
  - coreml
  - apple-neural-engine
  - palettized
  - tokforge
base_model:
  - SG161222/Realistic_Vision_V5.1_noVAE
pipeline_tag: text-to-image
library_name: ml-stable-diffusion

LocalMuseAI distribution mirror

This repository is an unmodified distribution mirror of darkmaniac7/TokForge-RealisticVision-5.1-CoreML-6bit for the LocalMuse iOS app. The compiled Core ML binary artifacts are preserved unchanged. Model authorship, conversion credit, license terms, and the original model card are retained below.

TokForge

Runs on-device in the TokForge app.

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.