reference models add distilled and community sections

Signed-off-by: Vladimir Mandic <mandic00@live.com>
2026-09-19 09:14:35 +02:00 · 2025-10-23 20:59:48 -04:00
parent a86fb66989
commit adbff39ca5
7 changed files with 61 additions and 9 deletions
@@ -4,8 +4,10 @@

 - **Features**
  - **offline mode**: enable in *settings -> hugginface*  
-    enables fully offline mode where previously downloaded models are used as-is  
+    enables fully offline mode where previously downloaded models can be used as-is  
    *note*: must be enabled only after all packages have been installed and model has been run online at least once  
+  - **networks**: add additional sections for **Reference** models:
+    **Distilled** which shows distilled variants of base models and **Community** which shows community highlights  
 - **Backend**
  - switch to `torch==2.9` for *ipex, rocm and openvino*  
  - switch to `rocm==7.0` for nightlies  
@@ -26,6 +28,7 @@
  - video tab create `params.txt` with metadata  
  - fix full-screen image-viewer toolbar actions with control tab  
  - improve filename sanitization  
+  - fix networks display with extended characters, thanks @awsr  

 ## Update for 2025-10-18

@@ -3,12 +3,18 @@
    "path": "tempestByVlad_baseV01.safetensors@https://civitai.com/api/download/models/1301775",
    "preview": "tempestByVlad_baseV01.jpg",
    "desc": "Flexible SDXL model with custom encoder and finetuned for larger landscape resolutions with high details and high contrast.",
+    "tags": "community",
+    "size": 6.94,
+    "date": "2025 January",
    "extras": ""
  },
  "Tempest-by-Vlad XL Hyper": {
    "path": "tempestByVlad_hyperV01.safetensors@https://civitai.com/api/download/models/1343512",
    "preview": "tempestByVlad_hyperV01.jpg",
    "desc": "Custom distilled variant with goal to get as-normal-as-possible model that works with low steps and guidance-free",
+    "tags": "community",
+    "size": 6.94,
+    "date": "2025 January",
    "extras": ""
  },

@@ -16,12 +22,18 @@
    "path": "juggernautXL_juggXIByRundiffusion.safetensors@https://civitai.com/api/download/models/782002",
    "preview": "juggernautXL_juggXIByRundiffusion.jpg",
    "desc": "Showcase finetuned model based on Stable diffusion XL",
+    "date": "2024 August",
+    "size": 6.94,
+    "tags": "community",
    "extras": "sampler: DEIS, steps: 20, cfg_scale: 6.0"
  },
  "Juggernaut XL XI Lightning": {
    "path": "juggernautXL_juggXILightningByRD.safetensors@https://civitai.com/api/download/models/920957",
    "preview": "juggernautXL_juggXILightningByRD.jpg",
    "desc": "Showcase finetuned model based on Stable diffusion XL",
+    "date": "2024 August",
+    "size": 6.94,
+    "tags": "community",
    "extras": "sampler: DPM SDE, steps: 6, cfg_scale: 2.0"
  },
  "Juggernaut SD Reborn": {
@@ -29,6 +41,9 @@
    "path": "juggernaut_reborn.safetensors@https://civitai.com/api/download/models/274039",
    "preview": "juggernaut_reborn.jpg",
    "desc": "Showcase finetuned model based on Stable diffusion 1.5",
+    "date": "2023 December",
+    "size": 2.28,
+    "tags": "community",
    "extras": "width: 512, height: 512, sampler: DEIS, steps: 20, cfg_scale: 6.0"
  },

@@ -56,6 +71,8 @@
    "preview": "stabilityai--stable-diffusion-2-1.jpg",
    "skip": true,
    "variant": "fp16",
+    "size": 2.58,
+    "date": "2022 December",
    "desc": "This stable-diffusion-2 model is resumed from stable-diffusion-2-base (512-base-ema.ckpt) and trained for 150k steps using a v-objective on the same dataset. Resumed for another 140k steps on 768x768 images",
    "extras": "width: 768, height: 768, sampler: DEIS, steps: 20, cfg_scale: 6.0"
  },
@@ -75,6 +92,7 @@
    "desc": "SDXL-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a 1-4 steps.",
    "skip": true,
    "variant": "fp16",
+    "tags": "distilled",
    "extras": "steps: 4, cfg_scale: 0.0"
  },
  "StabilityAI Stable Cascade": {
@@ -95,6 +113,7 @@
    "preview": "stabilityai--stable-cascade-lite.jpg",
    "extras": "sampler: Default, cfg_scale: 4.0, image_cfg_scale: 1.0",
    "size": 4.97,
+    "tags": "distilled",
    "date": "2024 February"
  },
  "StabilityAI Stable Diffusion 3 Medium": {
@@ -133,6 +152,7 @@
    "variant": "fp16",
    "desc": "Stable Diffusion 3.5 Large Turbo is a Multimodal Diffusion Transformer (MMDiT) text-to-image model with Adversarial Diffusion Distillation (ADD) that features improved performance in image quality, typography, complex prompt understanding, and resource-efficiency, with a focus on fewer inference steps.",
    "preview": "stabilityai--stable-diffusion-3_5-large-turbo.jpg",
+    "tags": "distilled",
    "extras": "sampler: Default, cfg_scale: 7.0"
  },

@@ -176,6 +196,7 @@
    "path": "vladmandic/flux.1-dev-SRPO",
    "preview": "vladmandic--flux.1-dev-SRPO.jpg",
    "desc": "FLUX.1 Dev SRPO is Tencent trained with specific technique: Directly Aligning the Full Diffusion Trajectory with Fine-Grained Human Preference",
+    "tags": "distilled",
    "skip": true,
    "extras": "sampler: Default, cfg_scale: 4.5"
  },
@@ -214,6 +235,7 @@
    "skip": true,
    "extras": "steps: 8",
    "size": 56.1,
+    "tags": "distilled",
    "date": "2025 August"
  },
  "Qwen-Image-Distill": {
@@ -223,6 +245,7 @@
    "skip": true,
    "extras": "steps: 15",
    "size": 56.1,
+    "tags": "distilled",
    "date": "2025 August"
  },
  "Qwen-Image-Lightning-Edit": {
@@ -232,6 +255,7 @@
    "skip": true,
    "extras": "steps: 8",
    "size": 56.1,
+    "tags": "distilled",
    "date": "2025 August"
  },
  "Qwen-Image Pruning-12B": {
@@ -240,6 +264,7 @@
    "preview": "OPPOer--Qwen-Image-Pruning.jpg",
    "desc": "This open-source project is based on Qwen-Image and has attempted model pruning, removing 20 layers while retaining the weights of 40 layers, resulting in a model size of 12B parameters.",
    "skip": true,
+    "tags": "distilled",
    "date": "2025 Ocotober"
  },
  "Qwen-Image-Edit Pruning-13B": {
@@ -248,6 +273,7 @@
    "preview": "OPPOer--Qwen-Image-Edit-Pruning.jpg",
    "desc": "This open-source project is based on Qwen-Image-Edit and has attempted model pruning, removing 20 layers while retaining the weights of 40 layers, resulting in a model size of 13.6B parameters.",
    "skip": true,
+    "tags": "distilled",
    "date": "2025 Ocotober"
  },
  "Qwen-Image-Edit-2509 Pruning-13B": {
@@ -256,6 +282,7 @@
    "preview": "OPPOer--Qwen-Image-Edit-2509-Pruning.jpg",
    "desc": "This open-source project is based on Qwen-Image-Edit and has attempted model pruning, removing 20 layers while retaining the weights of 40 layers, resulting in a model size of 13.6B parameters.",
    "skip": true,
+    "tags": "distilled",
    "date": "2025 Ocotober"
  },

@@ -284,6 +311,7 @@
    "skip": true,
    "extras": "",
    "size": 26.84,
+    "tags": "distilled",
    "date": "2025 July"
  },
  "lodestones Chroma1 v50 Preview Annealed": {
@@ -419,6 +447,7 @@
    "preview": "SDXL-Flash_Mini.jpg",
    "desc": "Introducing the new fast model SDXL Flash (Mini), we learned that all fast XL models work fast, but the quality decreases, and we also made a fast model, but it is not as fast as LCM, Turbo, Lightning and Hyper, but the quality is higher.",
    "extras": "width: 2048, height: 1024, sampler: DEIS, steps: 40, cfg_scale: 6.0",
+    "tags": "distilled",
    "experimental": true
  },

@@ -442,6 +471,7 @@
    "path": "Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers",
    "desc": "SANA-Sprint is an ultra-efficient diffusion model for text-to-image (T2I) generation, reducing inference steps from 20 to 1-4 while achieving state-of-the-art performance.",
    "preview": "Efficient-Large-Model--Sana15_Sprint_1600M_1024px_diffusers.jpg",
+    "tags": "distilled",
    "skip": true
  },
  "NVLabs Sana 1.0 1.6B 4k": {
@@ -555,6 +585,7 @@
    "skip": true,
    "extras": "sampler: Default, cfg_scale: 9.0",
    "size": 8.72,
+    "tags": "distilled",
    "date": "2023 October"
  },
  "Segmind Tiny": {
@@ -563,6 +594,7 @@
    "desc": "Segmind's Tiny-SD offers a compact, efficient, and distilled version of Realistic Vision 4.0 and is up to 80% faster than SD1.5",
    "extras": "width: 512, height: 512, sampler: Default, cfg_scale: 9.0",
    "size": 1.03,
+    "tags": "distilled",
    "date": "2023 July"
  },
  "Segmind SegMoE SD 4x2": {
@@ -627,6 +659,7 @@
    "path": "Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers-Distilled",
    "desc": "Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.",
    "preview": "Tencent-Hunyuan--HunyuanDiT-v1.2-Diffusers-Distilled.jpg",
+    "tags": "distilled",
    "extras": "sampler: Default, cfg_scale: 2.0"
  },
  "Tencent HunyuanDiT 1.1": {
@@ -639,6 +672,7 @@
    "path": "Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled",
    "desc": "Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.",
    "preview": "Tencent-Hunyuan--HunyuanDiT-v1.1-Diffusers-Distilled.jpg",
+    "tags": "distilled",
    "extras": "sampler: Default, cfg_scale: 2.0"
  },

@@ -796,18 +830,21 @@
    "path": "shuttleai/shuttle-3-diffusion",
    "desc": "Shuttle uses Flux.1 Schnell as its base. It can produce images similar to Flux Dev or Pro in just 4 steps, and it is licensed under Apache 2. The model was partially de-distilled during training. When used beyond 10 steps, it enters refiner mode enhancing image details without altering the composition",
    "preview": "shuttleai--shuttle-3-diffusion.jpg",
+    "tags": "community",
    "skip": true
  },
  "ShuttleAI Shuttle 3.1 Aesthetic": {
    "path": "shuttleai/shuttle-3.1-aesthetic",
    "desc": "Shuttle uses Flux.1 Schnell as its base. It can produce images similar to Flux Dev or Pro in just 4 steps, and it is licensed under Apache 2. The model was partially de-distilled during training. When used beyond 10 steps, it enters refiner mode enhancing image details without altering the composition",
    "preview": "shuttleai--shuttle-3_1-aestetic.jpg",
+    "tags": "community",
    "skip": true
  },
  "ShuttleAI Shuttle Jaguar": {
    "path": "shuttleai/shuttle-jaguar",
    "desc": "Shuttle uses Flux.1 Schnell as its base. It can produce images similar to Flux Dev or Pro in just 4 steps, and it is licensed under Apache 2. The model was partially de-distilled during training. When used beyond 10 steps, it enters refiner mode enhancing image details without altering the composition",
    "preview": "shuttleai--shuttle-jaguar.jpg",
+    "tags": "community",
    "skip": true
  },

@@ -144,7 +144,15 @@ async function filterExtraNetworksForTab(searchTerm) {
    } else if (searchTerm === 'reference/') {
      cards.forEach((elem) => elem.style.display = elem.dataset.name
        .toLowerCase()
-        .includes('reference/') ? '' : 'none');
+        .includes('reference/') && elem.dataset.tags === '' ? '' : 'none');
+    } else if (searchTerm === 'distilled/') {
+      cards.forEach((elem) => elem.style.display = elem.dataset.tags
+        .toLowerCase()
+        .includes('distilled') ? '' : 'none');
+    } else if (searchTerm === 'community/') {
+      cards.forEach((elem) => elem.style.display = elem.dataset.tags
+        .toLowerCase()
+        .includes('community') ? '' : 'none');
    } else if (searchTerm === 'local/') {
      cards.forEach((elem) => elem.style.display = elem.dataset.name
        .toLowerCase()
@@ -170,7 +170,7 @@ async function initModels() {
    if (en.classList.contains('hide')) gradioApp().getElementById('txt2img_extra_networks_btn').click();
    const repeat = setInterval(() => {
      const buttons = Array.from(gradioApp().querySelectorAll('#txt2img_model_subdirs > button')) || [];
-      const reference = buttons.find((b) => b.innerText === 'Reference');
+      const reference = buttons.find((b) => (b.innerText === 'Reference') || (b.innerText === 'Distilled') || (b.innerText === 'Community'));
      if (reference) {
        clearInterval(repeat);
        reference.click();
@@ -255,11 +255,9 @@ class ExtraNetworksPage:
        for parentdir, dirs in {d: files_cache.walk(d, cached=True, recurse=files_cache.not_hidden) for d in allowed_folders}.items():
            for tgt in dirs:
                tgt = tgt.path
-                if os.path.join(paths.models_path, 'Reference') in tgt and shared.opts.extra_network_reference_enable:
-                    subdirs['Reference'] = 1
+                if os.path.join(paths.models_path, 'Reference') in tgt:
                    continue
                if shared.opts.diffusers_dir in tgt:
-                    subdirs[diffusers_base] = 1
                    continue
                if 'models--' in tgt:
                    continue
@@ -274,6 +272,8 @@ class ExtraNetworksPage:
        if self.name == 'model' and shared.opts.extra_network_reference_enable:
            subdirs['Local'] = 1
            subdirs['Reference'] = 1
+            subdirs['Distilled'] = 1
+            subdirs['Community'] = 1
            subdirs[diffusers_base] = 1
        if self.name == 'style' and shared.opts.extra_networks_styles:
            subdirs['Local'] = 1
@@ -287,12 +287,15 @@ class ExtraNetworksPage:
            subdirs.move_to_end(os.path.basename(shared.opts.diffusers_dir), last=True)
        if 'Reference' in subdirs:
            subdirs.move_to_end('Reference', last=True)
+        if 'Distilled' in subdirs:
+            subdirs.move_to_end('Distilled', last=True)
+        if 'Community' in subdirs:
+            subdirs.move_to_end('Community', last=True)
        subdirs_html = ''
        for subdir in subdirs:
            if len(subdir) == 0:
                continue
-            style = 'color: var(--color-accent)' if subdir in ['All', 'Local', 'Diffusers', 'Reference'] else ''
-            if subdir in ['All', 'Local', 'Diffusers', 'Reference']:
+            if subdir in ['All', 'Local', 'Diffusers', 'Reference', 'Distilled', 'Community']:
                style = 'network-reference'
            else:
                style = 'network-folder'
@@ -85,6 +85,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
                "metadata": {},
                "description": v.get('desc', ''),
                "version": "ready" if ready else "download",
+                "tags": v.get('tags', ''),
            }
        shared.log.debug(f'Networks: type="reference" items={count["total"]} ready={count["ready"]} hidden={count["hidden"]} experimental={count["experimental"]}')