update chroma to v48 and add detailed and flash variants

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -6,6 +6,9 @@
   - [FLUX.1-Krea-Dev](https://www.krea.ai/blog/flux-krea-open-source-release)  
     new 12B base model compatible with FLUX.1-Dev from Black Forest Labs with opinionated aesthetics and aesthetic preferences in mind  
     simply select in *networks -> models -> reference*  
+  - [Chroma](https://huggingface.co/lodestones/Chroma)  
+    update with latest **v48**, **v48 Detail Calibrated** and **v46 Flash** variants  
+    simply select in *networks -> models -> reference*  
 - **Feature**  
   - **Wan** select which stage to run: *first/second/both* with configurable *boundary ration* when running both stages  
     in settings -> model options  
@@ -29,6 +32,7 @@
   - fix progress bar with refine/detailer  
   - fix api progress reporting endpoint  
   - fix openvino backend failing to compile  
+  - fix nunchaku fallback on unsupported model  
   - avoid forced gc and rely on thresholds  
   - add missing interrogate in output panel  
 

html/reference.json

@@ -173,13 +173,27 @@
     "extras": "sampler: Default, cfg_scale: 4.5"
   },
 
-  "lodestones Chroma": {
-    "path": "lodestones/Chroma",
+  "lodestones Chroma Unlocked v48": {
+    "path": "vladmandic/chroma-unlocked-v48",
     "preview": "lodestones--Chroma.jpg",
     "desc": "Chroma is a 8.9B parameter model based on FLUX.1-schnell. It’s fully Apache 2.0 licensed, ensuring that anyone can use, modify, and build on top of it—no corporate gatekeeping. The model is still training right now, and I’d love to hear your thoughts! Your input and feedback are really appreciated.",
     "skip": true,
     "extras": "sampler: Default, cfg_scale: 3.5"
   },
+  "lodestones Chroma Unlocked v48 Detail Calibrated": {
+    "path": "vladmandic/chroma-unlocked-v48-detail-calibrated",
+    "preview": "lodestones--Chroma.jpg",
+    "desc": "Chroma is a 8.9B parameter model based on FLUX.1-schnell. It’s fully Apache 2.0 licensed, ensuring that anyone can use, modify, and build on top of it—no corporate gatekeeping. The model is still training right now, and I’d love to hear your thoughts! Your input and feedback are really appreciated.",
+    "skip": true,
+    "extras": "sampler: Default, cfg_scale: 3.5"
+  },
+  "lodestones Chroma Unlocked v48 Flash": {
+    "path": "vladmandic/chroma-unlocked-v46-flash",
+    "preview": "lodestones--Chroma.jpg",
+    "desc": "Chroma is a 8.9B parameter model based on FLUX.1-schnell. It’s fully Apache 2.0 licensed, ensuring that anyone can use, modify, and build on top of it—no corporate gatekeeping. The model is still training right now, and I’d love to hear your thoughts! Your input and feedback are really appreciated.",
+    "skip": true,
+    "extras": "sampler: Default, cfg_scale: 1.0"
+  },
 
   "Ostris Flex.2 Preview": {
     "path": "ostris/Flex.2-preview",

installer.py

@@ -1216,7 +1216,7 @@ def ensure_base_requirements():
         update_setuptools()
 
     # used by installler itself so must be installed before requirements
-    install('rich==14.0.0', 'rich', quiet=True)
+    install('rich==14.1.0', 'rich', quiet=True)
     install('psutil', 'psutil', quiet=True)
     install('requests==2.32.3', 'requests', quiet=True)
     ts('base', t_start)

pipelines/model_chroma.py

@@ -117,7 +117,7 @@ def load_quants(kwargs, repo_id, cache_dir, allow_quant): # pylint: disable=unus
             "cache_dir": cache_dir,
         }
         if 'transformer' not in kwargs and model_quant.check_nunchaku('Model'):
-            raise NotImplementedError('Nunchaku does not support Chroma Model yet. See https://github.com/mit-han-lab/nunchaku/issues/167')
+            shared.log.error(f'Load module: quant=Nunchaku module=transformer repo="{repo_id}" unsupported')
         if 'transformer' not in kwargs and model_quant.check_quant('Model'):
             load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model', device_map=True, modules_to_not_convert=["distilled_guidance_layer"])
             kwargs['transformer'] = diffusers.ChromaTransformer2DModel.from_pretrained(repo_id, subfolder="transformer", **load_args, **quant_args)

requirements.txt

@@ -31,7 +31,7 @@ invisible-watermark
 pi-heif
 
 # versioned
-rich==14.0.0
+rich==14.1.0
 safetensors==0.5.3
 tensordict==0.8.3
 peft==0.16.0