fix ti

TODO.md

@@ -2,6 +2,10 @@
 
 Main ToDo list can be found at [GitHub projects](https://github.com/users/vladmandic/projects)
 
+## Fix
+
+- ultralytics package install
+
 ## Future Candidates
 
 - stable diffusion 3.0: unreleased
@@ -10,10 +14,22 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 - async lowvram: <https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14855>
 - fp8: <https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14031>
 - profiling: <https://github.com/lllyasviel/stable-diffusion-webui-forge/discussions/716>
+- kohya-hires-fix: <https://github.com/huggingface/diffusers/pull/7633>
+- hunyuan-dit: <https://github.com/huggingface/diffusers/pull/8290>
 - init latents: variations, img2img
 - diffusers public callbacks  
 - include reference styles
 - lora: sc lora, dora, etc
+
+## Experimental
+
+- [MuLan](https://github.com/mulanai/MuLan) Multi-langunage prompts - wirte your prompts in ~110 auto-detected languages!
+  Compatible with SD15 and SDXL
+  Enable in scripts -> MuLan and set encoder to `InternVL-14B-224px` encoder
+  (that is currently only supported encoder, but others will be added)
+  Note: Model will be auto-downloaded on first use: note its huge size of 27GB
+  Even executing it in FP16 context will require ~16GB of VRAM for text encoder alone
+  *Note*: Uses fixed prompt parser, so no prompt attention will be used
 - [SDXL Flash Mini](https://huggingface.co/sd-community/sdxl-flash-mini)  
   SDXL type that weighs less, consumes less video memory, and the quality has not dropped much  
   to use, simply select from *networks -> models -> reference -> SDXL Flash Mini*  

modules/textual_inversion/textual_inversion.py

@@ -140,7 +140,7 @@ class EmbeddingDatabase:
     def get_expected_shape(self):
         if shared.backend == shared.Backend.DIFFUSERS:
             return 0
-        if shared.sd_loaded:
+        if not shared.sd_loaded:
             shared.log.error('Model not loaded')
             return 0
         vec = shared.sd_model.cond_stage_model.encode_embedding_init_text(",", 1)