Instructions to use rityak/RealCore_Illustrious with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rityak/RealCore_Illustrious with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rityak/RealCore_Illustrious", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| language: | |
| - en | |
| pipeline_tag: text-to-image | |
| library_name: diffusers | |
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - safetensors | |
| - stable-diffusion-xl | |
| - merge | |
| license: openrail++ | |
| <style> | |
| /* ===== Hero section ===== */ | |
| .rc-hero { | |
| display: flex; | |
| gap: 1.75rem; | |
| align-items: flex-start; | |
| justify-content: center; | |
| max-width: 1100px; | |
| margin: 0 auto 2.25rem; | |
| flex-wrap: wrap; | |
| } | |
| .rc-hero-media, | |
| .rc-hero-details { | |
| flex: 1 1 320px; | |
| min-width: 0; | |
| } | |
| .rc-hero-media { | |
| display: flex; | |
| justify-content: center; | |
| } | |
| .rc-hero-video { | |
| width: 100%; | |
| max-width: 460px; | |
| border-radius: 8px; | |
| box-shadow: 0 8px 20px rgba(0, 0, 0, 0.25); | |
| overflow: hidden; | |
| } | |
| .rc-hero-title { | |
| margin: 0 0 0.6rem; | |
| font-size: 1.9rem; | |
| line-height: 1.2; | |
| color: var(--text-title, inherit); | |
| } | |
| .rc-hero-description { | |
| margin: 0 0 1.1rem; | |
| line-height: 1.5; | |
| font-size: 0.95rem; | |
| color: var(--text-normal, inherit); | |
| } | |
| .rc-hero-features { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0 0 1.2rem; | |
| font-size: 0.95rem; | |
| color: var(--text-normal, inherit); | |
| } | |
| .rc-hero-features li { | |
| display: flex; | |
| align-items: center; | |
| gap: 0.4rem; | |
| margin-bottom: 0.35rem; | |
| } | |
| .rc-hero-features .icon { | |
| font-size: 1.05rem; | |
| opacity: 0.9; | |
| } | |
| .rc-badge-list { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0; | |
| display: flex; | |
| flex-wrap: wrap; | |
| gap: 0.5rem; | |
| } | |
| .rc-badge-item { | |
| margin: 0; | |
| } | |
| .rc-badge-btn { | |
| display: inline-flex; | |
| align-items: center; | |
| height: 30px; | |
| padding: 0 11px; | |
| font-size: 0.85rem; | |
| font-weight: 500; | |
| text-decoration: none; | |
| border-radius: 4px; | |
| white-space: nowrap; | |
| transition: opacity 0.18s ease, transform 0.1s ease, background-color 0.18s ease; | |
| border: 1px solid transparent; | |
| background-color: transparent; | |
| color: var(--text-normal, inherit); | |
| } | |
| .rc-badge-btn-icon { | |
| width: 14px; | |
| height: 14px; | |
| margin-right: 6px; | |
| } | |
| .rc-badge-btn:hover { | |
| opacity: 0.9; | |
| transform: translateY(-1px); | |
| } | |
| .rc-badge-btn.civitai { | |
| border-color: #2975fa40; | |
| background-color: #2975fa1a; | |
| color: #2975fa; | |
| } | |
| .rc-badge-btn.hf { | |
| border-color: #ff660040; | |
| background-color: #ff66001a; | |
| color: #ff6600; | |
| } | |
| @media (max-width: 700px) { | |
| .rc-hero { | |
| margin-bottom: 1.75rem; | |
| } | |
| .rc-hero-video { | |
| max-width: 100%; | |
| } | |
| } | |
| /* ===== Model cards (компактные) ===== */ | |
| .models-container { | |
| display: grid; | |
| grid-template-columns: repeat(auto-fit, minmax(260px, 1fr)); | |
| gap: 1rem; | |
| padding: 0; | |
| margin: 0 0 1.75rem; | |
| } | |
| .model-card { | |
| border-radius: 8px; | |
| padding: 0.9rem 1rem; | |
| border: 1px solid var(--background-modifier-border, #dedede); | |
| background-color: var(--background-secondary, transparent); | |
| box-shadow: none; | |
| transition: border-color 0.18s ease, transform 0.1s ease; | |
| font-size: 0.9rem; | |
| } | |
| .model-card:hover { | |
| transform: translateY(-2px); | |
| border-color: var(--text-accent, #2975fa80); | |
| } | |
| .model-header { | |
| margin: 0 0 0.35rem; | |
| padding-bottom: 0.25rem; | |
| border-bottom: 1px solid var(--background-modifier-border, #e0e0e0); | |
| font-size: 0.95rem; | |
| font-weight: 600; | |
| color: var(--text-title, inherit); | |
| display: flex; | |
| align-items: center; | |
| justify-content: space-between; | |
| gap: 0.5rem; | |
| } | |
| .model-version { | |
| background: var(--background-modifier-border, #e0e0e0); | |
| color: var(--text-normal, #555); | |
| padding: 0.05rem 0.45rem; | |
| border-radius: 999px; | |
| font-size: 0.75rem; | |
| font-weight: 600; | |
| flex-shrink: 0; | |
| } | |
| .model-type { | |
| font-style: normal; | |
| font-size: 0.78rem; | |
| color: var(--text-muted, #777); | |
| margin-bottom: 0.55rem; | |
| display: block; | |
| } | |
| .model-base { | |
| font-weight: 600; | |
| color: var(--text-accent, #2975fa); | |
| } | |
| .model-description { | |
| margin: 0 0 0.7rem; | |
| line-height: 1.4; | |
| color: var(--text-normal, inherit); | |
| } | |
| .features-list { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0 0 0.75rem; | |
| font-size: 0.85rem; | |
| color: var(--text-normal, inherit); | |
| } | |
| .features-list li { | |
| display: flex; | |
| align-items: center; | |
| gap: 0.35rem; | |
| margin-bottom: 0.3rem; | |
| } | |
| .features-list .icon { | |
| font-size: 0.95rem; | |
| opacity: 0.9; | |
| } | |
| .badge-list { | |
| list-style: none; | |
| padding: 0; | |
| margin: 0; | |
| display: flex; | |
| flex-wrap: wrap; | |
| gap: 0.4rem; | |
| } | |
| .badge-list li { | |
| margin: 0; | |
| } | |
| .badge-btn { | |
| display: inline-flex; | |
| align-items: center; | |
| padding: 0 9px; | |
| height: 26px; | |
| font-size: 0.78rem; | |
| font-weight: 500; | |
| border-radius: 4px; | |
| text-decoration: none; | |
| border: 1px solid transparent; | |
| background-color: transparent; | |
| transition: opacity 0.18s ease, transform 0.1s ease, background-color 0.18s ease; | |
| color: var(--text-normal, inherit); | |
| } | |
| .badge-btn .btn-icon { | |
| width: 13px; | |
| height: 13px; | |
| margin-right: 5px; | |
| } | |
| .badge-btn:hover { | |
| opacity: 0.9; | |
| transform: translateY(-1px); | |
| } | |
| .badge-btn.civitai { | |
| border-color: #2975fa40; | |
| background-color: #2975fa12; | |
| color: #2975fa; | |
| } | |
| .badge-btn.hf { | |
| border-color: #ff660040; | |
| background-color: #ff660012; | |
| color: #ff6600; | |
| } | |
| /* ===== Repo links block ===== */ | |
| .repo-links { | |
| display: flex; | |
| flex-wrap: wrap; | |
| gap: 0.6rem; | |
| justify-content: center; | |
| margin: 1.75rem auto 0; | |
| padding: 1rem 1.25rem; | |
| max-width: 750px; | |
| border-radius: 10px; | |
| background: var(--background-secondary, rgba(0, 0, 0, 0.02)); | |
| border: 1px solid var(--background-modifier-border, #e0e0e0); | |
| } | |
| .repo-link { | |
| display: inline-flex; | |
| align-items: center; | |
| padding: 0.45rem 0.9rem; | |
| border-radius: 6px; | |
| font-size: 0.82rem; | |
| font-weight: 500; | |
| text-decoration: none; | |
| transition: opacity 0.18s ease, transform 0.1s ease, background-color 0.18s ease; | |
| border: 1px solid transparent; | |
| color: var(--text-normal, inherit); | |
| background-color: transparent; | |
| } | |
| .repo-link:hover { | |
| opacity: 0.9; | |
| transform: translateY(-1px); | |
| } | |
| .repo-link.hf { | |
| border-color: #ff660040; | |
| background-color: #ff660012; | |
| color: #ff6600; | |
| } | |
| .repo-link.civitai { | |
| border-color: #2975fa40; | |
| background-color: #2975fa12; | |
| color: #2975fa; | |
| } | |
| @media (max-width: 768px) { | |
| .repo-links { | |
| flex-direction: column; | |
| align-items: stretch; | |
| } | |
| .repo-link { | |
| justify-content: center; | |
| } | |
| } | |
| .rc-footer-note { | |
| text-align: center; | |
| margin-top: 1.75rem; | |
| padding: 0.75rem; | |
| font-size: 0.8rem; | |
| color: var(--text-muted, #6c757d); | |
| font-style: italic; | |
| } | |
| </style> | |
| <div class="rc-hero"> | |
| <div class="rc-hero-media"> | |
| <video | |
| class="rc-hero-video" | |
| controls | |
| autoplay | |
| loop | |
| muted | |
| playsinline | |
| preload="metadata" | |
| poster="https://huggingface.co/rityak/RealCore_Illustrious/resolve/main/img.png" | |
| > | |
| <source src="https://huggingface.co/rityak/RealCore_Illustrious/resolve/main/vid.mp4" type="video/mp4"> | |
| <img | |
| src="https://huggingface.co/rityak/RealCore_Illustrious/resolve/main/img.png" | |
| alt="Preview image of RealCore Illustrious model" | |
| style="width:100%; max-width:500px; border-radius:8px;" | |
| /> | |
| Your browser does not support the video tag. | |
| </video> | |
| </div> | |
| <div class="rc-hero-details"> | |
| <h1 class="rc-hero-title">RealCore Illustrious 1.0</h1> | |
| <p class="rc-hero-description"> | |
| <strong>RealCore Illustrious</strong> is a merged <strong>Illustrious</strong> checkpoint built from multiple models and LoRAs, | |
| designed to deliver stunning results in <em>realistic</em> and <em>photo-realistic</em> styles. | |
| Fully supports <strong>NSFW</strong> generation and integrates seamlessly with <strong>LCM</strong> acceleration. | |
| </p> | |
| <ul class="rc-hero-features"> | |
| <li><span class="icon">📷</span>Realistic & photo-realistic rendering</li> | |
| <li><span class="icon">🔀</span>Complex multi-model merge with LoRAs</li> | |
| <li><span class="icon">⚡</span>Excellent <strong>LCM</strong> compatibility</li> | |
| <li><span class="icon">🔓</span>NSFW supported</li> | |
| </ul> | |
| <ul class="rc-badge-list"> | |
| <li class="rc-badge-item"> | |
| <a | |
| href="https://civitai.com/models/2128436" | |
| target="_blank" | |
| class="rc-badge-btn civitai" | |
| > | |
| <img | |
| src="https://civitai.com/favicon-blue.ico" | |
| alt="CivitAI" | |
| class="rc-badge-btn-icon" | |
| /> | |
| View on CivitAI | |
| </a> | |
| </li> | |
| <li class="rc-badge-item"> | |
| <a | |
| href="https://huggingface.co/rityak/RealCore_Illustrious/resolve/main/RealCore_Illustrious_v10.safetensors?download=true" | |
| target="_blank" | |
| class="rc-badge-btn hf" | |
| > | |
| <img | |
| src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" | |
| alt="Hugging Face" | |
| class="rc-badge-btn-icon" | |
| /> | |
| Download RealCore Illustrious 1.0 | |
| </a> | |
| </li> | |
| </ul> | |
| </div> | |
| </div> | |
| ## 🧩 Model Overview | |
| **RealCore Illustrious** is a diffusion-based **Illustrious** checkpoint obtained through a complex merging process of multiple realistic models combined with several custom LoRAs. | |
| It produces highly detailed, lifelike, and emotionally grounded results — especially suited for **realistic**, **photo-realistic**, **nsfw**, and **professional photo** compositions. | |
| - **Type:** SDXL Merge | |
| - **Base:** Illustrious | |
| - **Supports:** Realistic / Photo-realistic / NSFW | |
| - **Optimized for:** ComfyUI + LCM | |
| --- | |
| ## ⚙️ ComfyUI Workflows | |
| | Workflow | Description | Link | | |
| | ------------ | -------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | |
| | **LCM DMD2** | Optimized for fast inference with LCM acceleration | <a href="https://huggingface.co/rityak/RealCore_Illustrious/resolve/main/RealCore%20Graph%20LCM.json?download=true" target="_blank">Download LCM DMD2 Workflow</a> | | |
| --- | |
| ## 🧠 Prompting | |
| For example prompts, styles, and tag guidance — please check | |
| 👉 [RealCore Illustrious on CivitAI](https://civitai.com/models/2128436) | |
| --- | |
| ## 🧾 Checkpoint Recipe | |
| ### RealCore Illustrious Beta Recipe | |
| ``` | |
| version 0.1.0 | |
| model "illustrious\\cyberrealistic_v70.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\goddessOfRealism_gorV6ilxlVAE.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\damnIllustriousPony_v50IllustriousNoobai.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\truespectraStudio_v10.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "🔨_weight_sum_with_json" &0 &1 &2 &3 json_params="{ | |
| \"global\": \"1.000,0.000,0.000,0.000\", | |
| \"CLIP_L\": \"0.250,0.250,0.250,0.250\", | |
| \"CLIP_G\": \"0.250,0.250,0.250,0.250\", | |
| \"time_embed\": \"0.250,0.250,0.250,0.250\", | |
| \"label_emb\": \"0.250,0.250,0.250,0.250\" | |
| }" | |
| merge "geometric_median" &0 &1 &2 &3 eps=1e-06 maxiter=100 ftol=1e-20 | |
| literal 1.0 model_config="sdxl-sgm" merge_space="param" | |
| merge "pick_component" &6 "clip_l" | |
| merge "pick_component" &6 "clip_g" | |
| merge "fallback" &7 &8 | |
| literal 0.0 model_config="sdxl-sgm" merge_space="param" | |
| merge "pick_component" &10 "vae" | |
| merge "fallback" &9 &11 | |
| merge "pick_component" &10 "diffuser" | |
| merge "fallback" &12 &13 | |
| merge "weighted_sum" &0 &5 &14 | |
| literal 0.5 model_config="sdxl-sgm" merge_space="param" | |
| merge "pick_component" &16 "clip_l" | |
| merge "pick_component" &16 "clip_g" | |
| merge "fallback" &17 &18 | |
| merge "fallback" &19 &11 | |
| merge "fallback" &20 &13 | |
| merge "crossover" &4 &15 &21 0.5 | |
| model "illustrious\\fantasticReality_10.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\illustriousXL_v01.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\realcosplay1024px_realcosplayV10Illust.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "subtract" &25 &24 | |
| model "illustrious\\realcosplay1536px_v21.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "subtract" &27 &24 | |
| model "illustrious\\illustriousCSG_unrealengineILProV1.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "subtract" &29 &24 | |
| model "illustrious\\illustriousFacial_v20.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "subtract" &31 &24 | |
| merge "geometric_median" &26 &28 &30 &32 eps=1e-06 maxiter=100 ftol=1e-20 | |
| merge "add_difference" &24 &33 1.0 | |
| merge "fallback" &34 &24 | |
| model "illustrious\\realistic\\Realim_Lora_BSY_IL_V1_RA42.safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &36 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &37 | |
| model "illustrious\\realistic\\Realistic_furry.safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &39 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &40 | |
| model "illustrious\\realistic\\ScreencUp.safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &42 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &43 | |
| merge "🔨_ties_lora_with_json" &38 &41 &44 json_params="{ | |
| \"lambda\": 1, | |
| \"weights\": \"0.500,0.500,0.500\", | |
| \"density\": 0.4, | |
| \"vote_sgn\": true, | |
| \"apply_stock\": false, | |
| \"apply_median\": true | |
| }" | |
| merge "add_difference" &35 &45 1.0 | |
| merge "fallback" &46 &35 | |
| merge "crossover" &23 &47 0.66 1.0 | |
| merge "🔨_karcher_mean_with_json" &0 &1 &3 json_params="{ | |
| \"global\": \"0.382,0.382,0.236\", | |
| \"max_iter\": 30, | |
| \"tol\": 3e-7 | |
| }" | |
| model "illustrious\\realistic\\ALTGRL(CYBERILL).safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &50 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &51 | |
| model "illustrious\\realistic\\RSGRL-REALLUXURA(10_10_25).safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &53 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &54 | |
| model "illustrious\\realistic\\KRGRLv2-000003.safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &56 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &57 | |
| merge "🔨_ties_lora_with_json" &52 &55 &58 json_params="{ | |
| \"lambda\": 1, | |
| \"weights\": \"0.500,0.500,0.200\", | |
| \"density\": 0.5, | |
| \"vote_sgn\": true, | |
| \"apply_stock\": false, | |
| \"apply_median\": true | |
| }" | |
| merge "add_difference" &49 &59 1.0 | |
| merge "fallback" &60 &49 | |
| merge "🔨_karcher_mean_with_json" &22 &48 &61 &2 json_params="{ | |
| \"global\": \"0.000,0.260,0.460,0.280\", | |
| \"max_iter\": 30, | |
| \"tol\": 3e-7, | |
| \"OUT04\": \"0.000,0.157,0.375,0.468\", | |
| \"OUT05\": \"0.000,0.157,0.375,0.468\", | |
| \"OUT06\": \"0.000,0.157,0.375,0.468\", | |
| \"IN\": \"0.000,0.230,0.477,0.294\", | |
| \"OUT\": \"0.000,0.273,0.312,0.415\", | |
| \"CLIP_L\": \"0.364,0.091,0.273,0.273\", | |
| \"CLIP_G\": \"0.364,0.091,0.273,0.273\" | |
| }" | |
| model "illustrious\\realistic\\FLMGR-IL.safetensors" model_config="sdxl-kohya_kohya_lora" merge_space="weight" | |
| merge "convert_'sdxl-kohya_kohya_lora'_to_base" &63 | |
| merge "convert_'sdxl-kohya'_to_'sdxl-sgm'" &64 | |
| dict BASE=0.0 IN00=0.0 IN01=0.0 IN02=0.0 IN03=0.0 IN04=0.0 IN05=0.0 IN06=0.0 IN07=0.0 IN08=0.0 M00=0.0 OUT00=0.0 OUT01=0.0 OUT02=0.15 OUT03=0.3 OUT04=0.4 OUT05=0.5 OUT06=0.3 OUT07=0.15 OUT08=0.0 VAE=0.0 | |
| literal &66 model_config="sdxl-supermerger_blocks" merge_space="param" | |
| merge "convert_sdxl_blocks_to_sgm" &67 | |
| merge "add_difference" &62 &65 &68 | |
| merge "fallback" &69 &62 | |
| ``` | |
| ### RealCore Illustrious v10 Recipe | |
| ``` | |
| version 0.1.0 | |
| model "ritya\\RealCore_Illustrious_beta.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\cyberrealistic_v70.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| model "illustrious\\damnIllustriousPony_v50IllustriousNoobai.safetensors" model_config="sdxl-sgm" merge_space="weight" | |
| merge "🔨_karcher_mean_with_json" &0 &1 &2 json_params="{ | |
| \"global\": \"1.000,0.000,0.000\", | |
| \"max_iter\": 50, | |
| \"tol\": 1e-7, | |
| \"IN00\": \"0.143,0.429,0.429\", | |
| \"IN01\": \"0.189,0.406,0.406\", | |
| \"IN02\": \"0.211,0.395,0.395\", | |
| \"IN03\": \"0.250,0.375,0.375\", | |
| \"IN04\": \"0.311,0.345,0.345\", | |
| \"IN06\": \"0.360,0.320,0.320\", | |
| \"IN07\": \"0.390,0.305,0.305\", | |
| \"IN08\": \"0.399,0.301,0.301\", | |
| \"IN\": \"0.333,0.333,0.333\" | |
| }" | |
| ``` |