update requirements and changelog

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

CHANGELOG.md

@@ -4,16 +4,20 @@
 
 ### Highlights for 2025-04-02
 
-Brand new Video processing module with support for all latest models: **WAN21, Hunyuan, LTX, Cog, Allegro, Mochi1, Latte1** in both *T2V* and *I2V* workflows  
+Time for another major release with ~120 commits and [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) that spans several pages!
+
+*Highlights?*  
+Video...Brand new Video processing module with support for all latest models: **WAN21, Hunyuan, LTX, Cog, Allegro, Mochi1, Latte1** in both *T2V* and *I2V* workflows  
 And combined with *on-the-fly quantization*, support for *Local/Tiny/Remote* VAE, acceleration modules such as *FasterCache or PAB*, and more!  
+Models...And support for new models: **CogView-4**, **SANA 1.5**, 
 
-Also, support for new models: **CogView-4**, **SANA 1.5**, 
-
-Plus...
+*Plus...*  
 - New **Prompt Enhance** using LLM,
 - New **CLiP** models, improvements to **remote VAE**, additional wiki/docs/guides  
 - More quantization options and granular control  
-- Pretty big performance updates to a) Any model using DiT based architecture: new caching methods, b) ZLUDA: new attention methods, c) much lower LoRA memory usage    
+- Pretty big performance updates to a) Any model using DiT based architecture due to new caching methods, b) ZLUDA with new attention methods, c) LoRA with much lower memory usage  
+
+[ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867)
 
 ### Details for 2025-04-02
 
@@ -153,7 +157,7 @@ Plus...
   - updated [ZLUDA](https://github.com/vladmandic/sdnext/wiki/ZLUDA) guide  
   - updated [OpenVINO](https://github.com/vladmandic/sdnext/wiki/OpenVINO) guide  
   - updated [AMD-ROCm](https://github.com/vladmandic/sdnext/wiki/AMD-ROCm) guide  
-  - upte [Intel-ARC](https://github.com/vladmandic/sdnext/wiki/Intel-ARC) guide  
+  - updated [Intel-ARC](https://github.com/vladmandic/sdnext/wiki/Intel-ARC) guide  
 - **Fixes**  
   - fix installer not starting when older version of `rich` is installed  
   - fix circular imports when debug flags are enabled  

installer.py

@@ -538,7 +538,7 @@ def check_diffusers():
     t_start = time.time()
     if args.skip_all or args.skip_git or args.experimental:
         return
-    sha = '75d7e5cc459f66a53652445d5b281054b297680d' # diffusers commit hash
+    sha = 'e5c6027ef89ec1a2800c0421599da89d4820f2e4' # diffusers commit hash
     pkg = pkg_resources.working_set.by_key.get('diffusers', None)
     minor = int(pkg.version.split('.')[1] if pkg is not None else 0)
     cur = opts.get('diffusers_version', '') if minor > 0 else ''

modules/shared.py

@@ -407,7 +407,7 @@ options_templates.update(options_section(('sd', "Models & Loading"), {
     "sd_checkpoint_autodownload": OptionInfo(True, "Model auto-download on demand"),
     "stream_load": OptionInfo(False, "Model load using streams", gr.Checkbox),
     "diffusers_eval": OptionInfo(True, "Force model eval", gr.Checkbox, {"visible": False }),
-    "diffusers_to_gpu": OptionInfo(False, "Load model directly to GPU"),
+    "diffusers_to_gpu": OptionInfo(False, "Model Load model direct to GPU"),
     "disable_accelerate": OptionInfo(False, "Disable accelerate", gr.Checkbox, {"visible": False }),
     "sd_model_dict": OptionInfo('None', "Use separate base dict", gr.Dropdown, lambda: {"choices": ['None'] + list_checkpoint_titles(), "visible": False}, refresh=refresh_checkpoints),
     "sd_checkpoint_cache": OptionInfo(0, "Cached models", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1, "visible": not native }),

requirements.txt

@@ -41,18 +41,18 @@ torchsde==0.2.6
 antlr4-python3-runtime==4.9.3
 requests==2.32.3
 tqdm==4.67.1
-accelerate==1.5.2
+accelerate==1.6.0
 opencv-contrib-python-headless==4.9.0.80
 einops==0.4.1
 gradio==3.43.2
-huggingface_hub==0.29.3
+huggingface_hub==0.30.1
 numexpr==2.8.8
 numpy==1.26.4
 numba==0.59.1
 protobuf==4.25.3
 pytorch_lightning==1.9.4
 tokenizers==0.21.1
-transformers==4.50.1
+transformers==4.50.3
 urllib3==1.26.19
 Pillow==10.4.0
 timm==0.9.16