feat: Add Anima support (#860)

* Add Anima training support

* Update Anima modular training

* Use sample guidance for Anima

* Fix Anima sampling

* Limit Anima LoRA targets

* Convert Anima LoRA exports

* Fix Anima local loading

* Update Anima default model

* Pin upstream Anima diffusers

* Adjust template defaults to be consistent with other models. Update README

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Co-authored-by: Jaret Burkett (Ostris) <jaretburkett@gmail.com>

toolkit/config_modules.py

@@ -594,7 +594,7 @@ class TrainConfig:
         self.max_loss: Optional[float] = kwargs.get("max_loss", None)
 
 
-ModelArch = Literal['sd1', 'sd2', 'sd3', 'sdxl', 'pixart', 'pixart_sigma', 'auraflow', 'flux', 'flex1', 'flex2', 'lumina2', 'vega', 'ssd', 'wan21']
+ModelArch = Literal['sd1', 'sd2', 'sd3', 'sdxl', 'pixart', 'pixart_sigma', 'auraflow', 'flux', 'flex1', 'flex2', 'lumina2', 'vega', 'ssd', 'wan21', 'anima']
 
 
 class ModelConfig:

toolkit/prompt_utils.py

@@ -152,6 +152,10 @@ class PromptEmbeds:
         metadata = f.metadata()
         if metadata is not None and metadata.get("class_name", "") == "AdvancedPromptEmbeds":
             return AdvancedPromptEmbeds.load(path=path)
+        if metadata is not None and metadata.get("class_name", "") == "AnimaPromptEmbeds":
+            from extensions_built_in.diffusion_models.anima import AnimaPromptEmbeds
+
+            return AnimaPromptEmbeds.load(path=path)
         
         state_dict = load_file(path, device='cpu')
         text_embeds = []