Buckets:
| license: wtfpl | |
| # malcolmrey's Various AI Model, Architecture & Research Repository | |
| Welcome to the central research and asset repository of **malcolmrey**. This repository hosts cutting-edge tools, custom architectures, RefMod latent adapter systems, video synthesis engines, training configurations, benchmark suites, cinematic scripts, and comprehensive educational guides spanning **MiniMax-H3**, **FLUX.2 / Klein 9B**, **Qwen-Image 2.1**, **WAN 2.1**, **LTX-Video**, **Z-Image**, **SDXL**, and **Stable Diffusion**. | |
| Much of the training work here uses **[maltrainer](https://github.com/malcolmamal/maltrainer)**, malcolmrey's own LoRA trainer. | |
| --- | |
| ## 🧭 Repository Map & Quick Navigation | |
| | Section / Directory | Focus Area & Description | Key Resources & Direct Links | | |
| | :--- | :--- | :--- | | |
| | 🎬 **[`h3-center/`](h3-center/)** | **MiniMax-H3 Video & Cinema Hub**<br>Complete prompt guides, RefMod stacking, hybrid LoRA+RefMod containers, identity-LoRA epoch sweeps, 1,500+ character tests, and 9-episode Crossovers cinematic series. | • [Prompting Guide](h3-center/docs/MINIMAX_H3_PROMPTING_GUIDE.md)<br>• [RefMod Stacking Guide](h3-center/docs/MINIMAX_H3_REFMOD_STACKING_AND_MULTISUBJECT_GUIDE.md)<br>• [Hybrid LoRA+RefMod Guide](h3-center/docs/MINIMAX_H3_HYBRID_LORA_REFMOD_CONTAINERS_GUIDE.md)<br>• [Jinx LoRA Epoch Sweep & RefMod Stack](h3-center/docs/lora/README.md)<br>• [Multistacking Benchmark Demos](h3-center/docs/multistacking/README.md)<br>• [Known Characters Usability Index](h3-center/known-characters/INDEX.md)<br>• [Crossovers Cinema Series](h3-center/crossovers/README.md) | | |
| | 🎨 **[`klein9/`](klein9/)** | **FLUX.2 & Klein 9B RefMods**<br>Instant reference latent adapter ecosystem, custom ComfyUI nodes, CLI batch extractor, and benchmark suites. | • [RefMod Architecture Guide](klein9/docs/FLUX2_KLEIN9_REFMODS_GUIDE.md)<br>• [ComfyUI Node](klein9/comfyui/custom_nodes/ComfyUI-Flux2Klein9Mod/)<br>• [Batch Extractor Tool](klein9/generate_flux2_klein9_refmod.py)<br>• [Workflows](klein9/workflows/) \| [Visual Benchmarks](klein9/docs/VISUAL_BENCHMARKS_AND_COMPARISONS.md) | | |
| | 👁️ **[`qwen/`](qwen/)** | **Qwen-Image 2.1 Multimodal Hub**<br>Vision-Language (Qwen3-VL) conditioning architecture, reference strategy analysis, identity transfer, prompt engineering standards, edit samples, and a LoRA optimizer benchmark trained with maltrainer. | • [RefMod Compatibility & ViT Architecture](qwen/docs/QWEN_IMAGE_21_REFMOD_COMPATIBILITY_AND_VISION_ENCODER_ARCHITECTURE.md)<br>• [Reference Strategy & Prompting Guide](qwen/docs/QWEN_IMAGE_21_REFERENCE_STRATEGY_AND_PROMPTING_GUIDE.md)<br>• [LoRA Optimizer Benchmark (maltrainer)](qwen/docs/QWEN_IMAGE_21_LORA_OPTIMIZER_BENCHMARK.md)<br>• [Qwen Hub Overview](qwen/README.md) | | |
| | 🧪 **[`moss/`](moss/)** | **MOSS-Image LoRA Training**<br>Combined training: one dataset trained with AdamW 8-bit, Automagic3 and Prodigy at short lengths, merged into one LoRA soup and resized to rank 8. Trained with maltrainer. | • [Combined Optimizer Training Guide](moss/docs/MOSS_IMAGE_COMBINED_OPTIMIZER_TRAINING_GUIDE.md)<br>• [Member Templates](moss/templates/) (AdamW 8-bit, Automagic3, Prodigy) | | |
| | ⚡ **[`zimage-turbo-vs-base-training/`](zimage-turbo-vs-base-training/)** | **Z Image Base vs. Turbo Benchmark**<br>Head-to-head training comparison across OneTrainer, MalTrainer, and AI Toolkit with datasets and weights. | • [Benchmark Overview & Configs](zimage-turbo-vs-base-training/README.md)<br>• Datasets, AdamW/Prodigy configs, & `.safetensors` weights | | |
| | 🛠️ **[`training-scripts/`](training-scripts/)** | **Production Training Configs**<br>Ready-to-use recipes for OneTrainer, Musubi Tuner, AI Toolkit, and MalTrainer. | • [OneTrainer Templates](training-scripts/onetrainer/) (Ernie, FK9, Krea2, SDXL, Z-Image)<br>• [Musubi Pipelines](training-scripts/musubi/) (Ernie, LTX23)<br>• [AI Toolkit](training-scripts/aitoolkit/) (FK9, Ideogram 4, WAN, Z-Image)<br>• [MalTrainer](training-scripts/maltrainer/) (Qwen-Image 2.1, Z-Image) | | |
| | 🎥 **Sample Media & Benchmarks** | **Model Generation Sample Libraries**<br>High-fidelity outputs and verification test suites. | • [`ltx23-samples/`](ltx23-samples/) (20 LTX-Video 2.3 renders)<br>• [`ernie-samples/`](ernie-samples/) (`ernie-samples.zip`)<br>• [`samples/fk9/`](samples/fk9/) (Rose Byrne & Sydney Sweeney outputs)<br>• [`qwen/samples/edit/`](qwen/samples/edit/) (11 Qwen-Image 2.1 character edits) | | |
| | 🗂️ **[`datasets/`](datasets/)** | **Sample Training Datasets**<br>Small image sets used in the training experiments. | • [`datasets/jinx/`](datasets/jinx/) (19 images)<br>• [`datasets/karengillan/`](datasets/karengillan/) (22 images) | | |
| | 📚 **Guides & Articles** | **Comprehensive Knowledge Base**<br>In-depth technical guides for model training, optimization, and prompt engineering. | • [WAN 2.1 LoRA Training Tutorial](tutorials/wan-21-lora-training.md)<br>• [CivitAI Articles Collection](articles.md) | | |
| --- | |
| ## 🎬 MiniMax-H3 Center (`h3-center/`) | |
| The **MiniMax-H3 Center** is an all-in-one research laboratory and production studio for the MiniMax Hailuo 01 / H3 text-to-video, image-to-video (I2V), reference-to-video (R2V), and clip-to-video (C2V) architectures. | |
| ### 📖 In-Depth Guides & Technical Documentation | |
| - 📘 **[MiniMax-H3 Video Prompt Writing Guide (v1.3.0)](h3-center/docs/MINIMAX_H3_PROMPTING_GUIDE.md)**: The authoritative standard for prompting MiniMax-H3. Covers pinpoint actor casting, character tag binding (`<Subject 1>`), timestamped action choreography (`through 00:08.000`), diegetic soundscapes, non-diegetic audio rules, camera vectors, and anti-patterns. | |
| - 🧬 **[RefMod Stacking & Multi-Subject Architecture Guide](h3-center/docs/MINIMAX_H3_REFMOD_STACKING_AND_MULTISUBJECT_GUIDE.md)**: Guide on injecting multiple pre-encoded latent references (`.safetensors`), single-persona Triple-RefMod fidelity stacking, conceptual body shape boosters, dual-persona shared frame conditioning, dual audio lip-syncing, and polyphonic counterpoint duets. | |
| - 📦 **[Hybrid LoRA + RefMod Container Specification Guide](h3-center/docs/MINIMAX_H3_HYBRID_LORA_REFMOD_CONTAINERS_GUIDE.md)**: Technical guide and implementation for embedding both LoRA weights and RefMod reference latents in a single `.safetensors` file, fully compatible with standard LoRA loaders (Power Lora Loader) and dedicated dual ComfyUI loader nodes. | |
| - 🎬 **[Multi-Stacking Benchmark Demos & Video Suite](h3-center/docs/multistacking/README.md)**: Verified `.mp4` benchmarks demonstrating single-persona Triple RefMods (Billie Eilish), dual conversations (Billie & Miley Cyrus), simultaneous two-shots, dual audio conditioning, and counterpoint singing duets with local RefMod latent files. | |
| - 🔗 **[C2V Continuous Chain Generation Guide](h3-center/docs/C2V_CONTINUOUS_CHAIN_GUIDE.md)**: Pipeline for chaining 5-second to 15-second video clips losslessly into seamless continuous takes. | |
| - 🎵 **[Audio-Synchronized & C2V Music Videos Guide](h3-center/docs/MINIMAX_AUDIO_SYNC_AND_C2V_MUSIC_VIDEOS.md)**: Techniques for aligning video cadence and singing motion with pre-recorded vocal tracks. | |
| - ⚙️ **[RefMods Installation & Usage Guide](h3-center/docs/MINIMAX_H3_REFMODS_INSTALLATION_AND_USAGE_GUIDE.md)** & **[RefMod Creation Guide](h3-center/docs/MINIMAX_H3_REFMOD_CREATION_GUIDE.md)**: Step-by-step instructions for extracting RefMod `.safetensors` from images and loading them into ComfyUI pipelines. | |
| - ⚖️ **[RefMods vs. Reference Images Comparison](h3-center/docs/MINIMAX_REFMODS_VS_REFERENCE_IMAGES.md)**: Architectural analysis of speed, latent fidelity, and token efficiency comparing pre-computed RefMods against raw pixel reference workflows. | |
| - 🧪 **[Jinx Identity LoRA Epoch Sweep & RefMod Stack](h3-center/docs/lora/README.md)**: A/B of an identity LoRA (epochs 60 / 80 / final) against a single identity RefMod and both combined, with 6 verified `.mp4` clips. Findings: **RefMod + LoRA is the strongest identity lock**, epoch 60 is already enough, and the LoRA carries the Arcane art style along with the face. | |
| - 🐍 **RefMod generator script:** [`h3-center/docs/scripts/generate_refmod.py`](h3-center/docs/scripts/generate_refmod.py) | |
| ### 👥 Known Characters & Usability Database | |
| - 📊 **[Usability Index (INDEX.md)](h3-center/known-characters/INDEX.md)** & **[Unusable Index (INDEX_BAD.md)](h3-center/known-characters/INDEX_BAD.md)**: Empirical test results evaluating over **1,500+** characters, actors, and public figures directly in MiniMax-H3: | |
| - **Good (540+ subjects):** Characters with zero-shot likeness locks (e.g., House, Dexter, Michael Scott, Walter White, Gandalf, Wednesday Addams, Dean Winchester). | |
| - **On the Fence (90+ subjects):** Subjects requiring targeted prompt tuning or RefMod assistance. | |
| - **Bad (920+ subjects):** Subjects that fail without custom LoRAs or dedicated RefMods. | |
| ### 🎥 Crossovers Episodic Cinema Series | |
| - 🍿 **[Crossovers Series Master Catalog](h3-center/crossovers/README.md)**: 9 narrative episodes created with MiniMax-H3, with cast listings and synopses (8 rendered `.mp4` files in the repo): | |
| - **Episode 1:** *The Contagion of Secrets* (House, Monk, Dwight, Dexter, Malcolm Reynolds, Mulder, Penny) | |
| - **Episode 2:** *The Cosmic Extradition* (Dean Winchester, Mal Reynolds, Sherlock, Pam Beesly, Lucifer, 10th Doctor, Saul Goodman, Steve Rogers, John Locke, Tony Stark) | |
| - **Episode 3:** *Lockdown at Sabre Tower* (Michael Scott, Wednesday Addams, John McClane, Seeley Booth, James Bond, Steve Rogers, Elliot Alderson, Lucifer, Jack Bauer) | |
| - **Episode 4:** *The War for the Obsidian Portal* (Maleficent, Daenerys, Gandalf, Dr. Strange, Hermione, Maximus, Jack Sparrow) | |
| - **Episode 5:** *The Flat Earth Experience* (Joe Rogan, Kanye West, Neil deGrasse Tyson, Dave Chappelle, Sir Anthony Hopkins) | |
| - **Episode 6:** *Dave Chappelle: The Flat Earth Special* (Stand-up comedy special) | |
| - **Episode 7:** *Dr. Robert Ford: On Meaning* (Philosophical monologue from Westworld) | |
| - **Episode 8:** *Ellis Boyd 'Red' Redding: On Hope and Love* (Shawshank monologue) | |
| - **Episode 9:** *Captain Malcolm Reynolds: Alone on Serenity* (Firefly character study) | |
| - 📚 **[Show & Character Guides (`h3-center/crossovers/docs/shows/`)](h3-center/crossovers/docs/shows/)**: Over **250+** show guides detailing character wardrobe, distinctive traits, and scene rules. | |
| --- | |
| ## 🎨 FLUX.2 & Klein 9B RefMods (`klein9/`) | |
| **RefMods (Reference Latent Adapters)** provide zero-shot facial fidelity and concept locking for **FLUX.2**, **Klein 4B**, **Klein 8B**, and **Klein 9B** without the VRAM overhead or training time required by full fine-tunes or LoRAs. | |
| - 🌐 **Interactive Model Browser:** [https://huggingface.co/spaces/malcolmrey/browser](https://huggingface.co/spaces/malcolmrey/browser) (Explore 1,400+ pre-extracted RefMods) | |
| - 🤗 **Model Weights Hub:** [https://huggingface.co/malcolmrey/klein9](https://huggingface.co/malcolmrey/klein9) (Download `.safetensors` adapters) | |
| - 🔌 **ComfyUI Custom Node:** [`klein9/comfyui/custom_nodes/ComfyUI-Flux2Klein9Mod/`](klein9/comfyui/custom_nodes/ComfyUI-Flux2Klein9Mod/) (Also available on [GitHub](https://github.com/malcolmamal/ComfyUI-Flux2Klein9Mod)) | |
| - ⚡ **CLI Generator & Mass Batch Extractor:** [`klein9/generate_flux2_klein9_refmod.py`](klein9/generate_flux2_klein9_refmod.py) | |
| - 📑 **Architecture & Extraction Guide:** [`klein9/docs/FLUX2_KLEIN9_REFMODS_GUIDE.md`](klein9/docs/FLUX2_KLEIN9_REFMODS_GUIDE.md) | |
| - 📊 **Visual Benchmarks & Comparisons:** [`klein9/docs/VISUAL_BENCHMARKS_AND_COMPARISONS.md`](klein9/docs/VISUAL_BENCHMARKS_AND_COMPARISONS.md) | |
| - 🔄 **Production Workflows:** | |
| - Pure RefMod Text-to-Image: [`klein9/workflows/workflow_klein9_refmod.json`](klein9/workflows/workflow_klein9_refmod.json) | |
| - Hybrid RefMod + LoRA Stack: [`klein9/workflows/workflow_klein9_refmod_lora.json`](klein9/workflows/workflow_klein9_refmod_lora.json) | |
| - 🖼️ **Sample Generations:** [`samples/fk9/`](samples/fk9/) (Rose Byrne and Sydney Sweeney benchmark runs) | |
| --- | |
| ## 👁️ Qwen-Image 2.1 Multimodal Hub (`qwen/`) | |
| The **Qwen-Image 2.1 Hub** covers empirical research and architectural standards for image generation and character identity transfer using the **Qwen-Image 2.1 Diffusion Transformer + Qwen3-VL Vision-Language conditioning pipeline**. | |
| ### 📖 Technical Documentation & Guides | |
| - 📘 **[RefMod Compatibility & Vision-Language Architecture Analysis](qwen/docs/QWEN_IMAGE_21_REFMOD_COMPATIBILITY_AND_VISION_ENCODER_ARCHITECTURE.md)**: Details why pre-encoded VAE RefMod adapters (`.safetensors` from MiniMax-H3 / FLUX.2) are mathematically incompatible with Qwen-Image 2.1, explaining Qwen3-VL's live ViT patch projection, dynamic token insertion, and joint cross-attention. | |
| - 📋 **[Reference Strategy, Prompting Standards & Identity Preservation Guide](qwen/docs/QWEN_IMAGE_21_REFERENCE_STRATEGY_AND_PROMPTING_GUIDE.md)**: Complete empirical benchmarking of reference strategies: | |
| - Demonstrates why **1 Reference Image per Person** is the optimal standard. | |
| - Documents failure modes of multi-image referencing for single subjects (token dilution, feature blending). | |
| - Documents failure modes of 2x2 and 3x3 composite grids (grid leak, loss of high-frequency skin textures). | |
| - Provides master production prompt templates for precision face-swapping (preserving body, pose, age, skin pores, and clothing) and multi-character scenes. | |
| - 🏋️ **[LoRA Optimizer Benchmark: AdamW vs Prodigy vs Automagic3](qwen/docs/QWEN_IMAGE_21_LORA_OPTIMIZER_BENCHMARK.md)**: Two-subject LoRA benchmark (Felicia Day, Rhea Seehorn) trained with **[maltrainer](https://github.com/malcolmamal/maltrainer)** on one RTX 5090 directly from the ComfyUI INT8 checkpoints. Every checkpoint was scored for likeness (ArcFace), prompt adherence (Qwen3-VL judge), seed diversity and memorization. | |
| - **Recommended: Automagic3, ~1500 steps (60–80 epochs), ≈13–16 minutes.** Likeness plateaus by ~1250 steps and stays flat, with the best prompt adherence and the smallest adapter. | |
| - Likeness is a tie across optimizers; Prodigy's learning rate keeps climbing until it memorizes the training set and ignores the prompt. | |
| - Caption finding: if captions say only "a woman …", the trigger never learns gender, so prompt with `"<trigger>, a woman, …"`. | |
| - Ready-to-use config: [`training-scripts/maltrainer/qwen_image_2_1_template.yaml`](training-scripts/maltrainer/qwen_image_2_1_template.yaml) | |
| ### 🖼️ Samples | |
| - **[`qwen/samples/edit/`](qwen/samples/edit/)**: 11 Qwen-Image 2.1 reference-edit outputs placing actors into iconic roles (e.g. Al Pacino as Tony Montana, Charlize Theron as Furiosa, Mads Mikkelsen as Hannibal Lecter, Gillian Anderson as Dana Scully). | |
| --- | |
| ## ⚡ Z Image Base vs. Z Image Turbo Training Suite (`zimage-turbo-vs-base-training/`) | |
| An empirical training study benchmarking **Z Image (Base)** against **Z Image (Turbo)** using identical curated datasets (Felicia Day, Olivia). | |
| - 📋 **[Overview & Documentation](zimage-turbo-vs-base-training/README.md)** | |
| - 📁 **Dataset:** [Curated 23-image high-resolution dataset](https://huggingface.co/datasets/malcolmrey/various/tree/main/zimage-turbo-vs-base-training/dataset) | |
| - ⚙️ **OneTrainer Configs:** AdamW and Prodigy optimization profiles (`.json`) | |
| - 🤖 **MalTrainer & AI Toolkit Recipes:** Full training configurations (`.yaml`) | |
| - 📦 **Trained Weights:** Verified `.safetensors` models for both Base and Turbo versions | |
| --- | |
| ## 🛠️ Production Training Scripts & Templates (`training-scripts/`) | |
| Curated configurations for high-efficiency model training across popular trainers: | |
| - 🟢 **[OneTrainer (`training-scripts/onetrainer/`)](training-scripts/onetrainer/)**: | |
| - `fk9_template.json` & `fk9_prodigy_template.json` — Klein 9B / FLUX.2 LoRA templates | |
| - `ernie_template.json` — Ernie training configuration | |
| - `krea2_template.json` & `krea2prodigy_template.json` — Krea 2 templates | |
| - `sdxl_template.json` & `sdxl_prodigy_template.json` — SDXL templates | |
| - `zimage_base_template.json` & `zimage_turbo_template.json` — Z-Image Base / Turbo templates | |
| - 🟣 **[Musubi Tuner (`training-scripts/musubi/`)](training-scripts/musubi/)**: | |
| - `musubi/ernie/` — Multi-resolution Ernie training scripts | |
| - `musubi/ltx23/` — LTX-Video 2.3 video model training configurations | |
| - 🔵 **[AI Toolkit (`training-scripts/aitoolkit/`)](training-scripts/aitoolkit/)**: | |
| - `fk9_template.yaml` & `fk9r_template.yaml` — Klein 9B / FLUX.2 | |
| - `ideogram4_template.yaml` — Ideogram 4 | |
| - `wan_template.yaml` — WAN 2.1 | |
| - `zimage_template.yaml`, `zbase_template.yaml` & `zonetrainer_template.yaml` — Z-Image variants | |
| - 🟠 **[MalTrainer (`training-scripts/maltrainer/`)](training-scripts/maltrainer/)** — configs for **[maltrainer](https://github.com/malcolmamal/maltrainer)**, malcolmrey's own trainer: | |
| - `qwen_image_2_1_template.yaml` — Qwen-Image 2.1 LoRA, the benchmark's recommended setting (Automagic3, ~1500 steps). Trains directly on the ComfyUI INT8 checkpoints. See the [optimizer benchmark](qwen/docs/QWEN_IMAGE_21_LORA_OPTIMIZER_BENCHMARK.md). | |
| - `zimage_base_template.yaml` — Z-Image Base LoRA | |
| --- | |
| ## 🎥 Video Samples & Benchmarks | |
| - 🎞️ **[`ltx23-samples/`](ltx23-samples/)**: 20 full-motion test videos evaluating coherence, prompt fidelity, and motion dynamics with **LTX-Video 2.3**. | |
| - 📦 **[`ernie-samples/`](ernie-samples/)**: Comprehensive benchmark sample package (`ernie-samples.zip`). | |
| - 🎬 **[`h3-center/crossovers/`](h3-center/crossovers/)**: 8 rendered `.mp4` full narrative crossover episodes. | |
| - 🎼 **[`h3-center/docs/multistacking/`](h3-center/docs/multistacking/)**: 8 dual-audio and counterpoint singing benchmark videos. | |
| - 🧪 **[`h3-center/docs/lora/`](h3-center/docs/lora/README.md)**: 6 Jinx identity-LoRA / RefMod comparison clips (5 s, 1344×768). | |
| - 🎤 **[`h3-center/docs/examples/`](h3-center/docs/examples/)**: 6 Billie Eilish / Miley Cyrus speech, singing and two-shot test clips. | |
| - 🗜️ **[`ltx-artifacts.zip`](ltx-artifacts.zip)**: 107 MB archive of LTX-Video material. | |
| --- | |
| ## 🗂️ Sample Datasets (`datasets/`) | |
| Small image sets used in the training experiments (images only, no caption files): | |
| - **[`datasets/jinx/`](datasets/jinx/)** — 19 images (Jinx / Arcane) | |
| - **[`datasets/karengillan/`](datasets/karengillan/)** — 22 images (Karen Gillan) | |
| --- | |
| ## 📚 Tutorials & Articles Collection | |
| ### 📘 [WAN 2.1 LoRA Training Tutorial](tutorials/wan-21-lora-training.md) | |
| Complete step-by-step guide on training WAN 2.1 LoRA models using AI Toolkit: | |
| - Dataset preparation (20 optimal images, 2500 steps) | |
| - Resolution bucketing & learning rate schedules | |
| - VRAM management & cloud GPU configurations | |
| - ComfyUI inference workflow integration | |
| ### 📚 [CivitAI Articles Collection](articles.md) | |
| Curated directory of malcolmrey's published training and generation guides: | |
| - **[DreamBooth / LyCORIS / LoRA Complete Guide](https://civitai.com/articles/7/dreambooth-lycoris-lora-guide)** | |
| - **[SDXL LoRA Training on RunPod](https://civitai.com/articles/1591/sdxl-lora-training)** | |
| - **[Textual Inversion / Embedding Training Guide](https://civitai.com/articles/3114/textual-inversion-embedding-training-guide)** | |
| - **[Flux Guide, Part I - LoRA Training](https://civitai.com/articles/9360/flux-guide-part-i-lora-training)** | |
| - **[Improving Results with Multi-Model Blending (Turning it to 11!)](https://civitai.com/articles/1721/improving-results-by-using-multiple-models-of-the-same-concept-turning-it-to-11)** | |
| - **[Quality Deep Dive (Bringing it up to Twelve!)](https://civitai.com/articles/3527/bringing-it-up-to-twelve-going-deep-into-quality)** | |
| - **[ADetailer, Inpainting & Facial Restoration Best Practices](https://civitai.com/articles/1633/adetailer-and-a-poll-and-a-few-words-about-roop)** | |
| --- | |
| ## 🌐 Connect with malcolmrey | |
| - 💬 **Discord Community:** [malcolmrey's place](https://discord.gg/RjYRPRCqu) | |
| - ☕ **Support / Priority Requests:** [Buy Me a Coffee](https://buymeacoffee.com/malcolmrey) | |
| - 🤗 **Hugging Face Hub:** [https://huggingface.co/malcolmrey](https://huggingface.co/malcolmrey) | |
| - 🔍 **Interactive Model Browser:** [https://huggingface.co/spaces/malcolmrey/browser](https://huggingface.co/spaces/malcolmrey/browser) | |
| - 🎨 **CivitAI Profile:** [https://civitai.com/user/malcolmrey](https://civitai.com/user/malcolmrey) | |
| - 💬 **Reddit Community:** [r/malcolmrey](http://reddit.com/r/malcolmrey) | |
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