AnimaTextConditioner .from_single_file() support

src/diffusers/loaders/single_file_model.py

@@ -36,6 +36,7 @@
     convert_autoencoder_dc_checkpoint_to_diffusers,
     convert_chroma_transformer_checkpoint_to_diffusers,
     convert_controlnet_checkpoint,
+    convert_anima_text_conditioner_to_diffusers,
     convert_cosmos_transformer_checkpoint_to_diffusers,
     convert_ernie_image_transformer_checkpoint_to_diffusers,
     convert_flux2_transformer_checkpoint_to_diffusers,
@@ -192,6 +193,10 @@
         "checkpoint_mapping_fn": convert_cosmos_transformer_checkpoint_to_diffusers,
         "default_subfolder": "transformer",
     },
+    "AnimaTextConditioner": {
+        "checkpoint_mapping_fn": convert_anima_text_conditioner_to_diffusers,
+        "default_subfolder": "text_conditioner",
+    },
     "QwenImageTransformer2DModel": {
         "checkpoint_mapping_fn": lambda checkpoint, **kwargs: checkpoint,
         "default_subfolder": "transformer",

src/diffusers/loaders/single_file_utils.py

@@ -3721,6 +3721,14 @@ def swap_scale_shift(weight):
 
     return converted_state_dict
 
+def convert_anima_text_conditioner_to_diffusers(checkpoint, **kwargs):
+    converted_state_dict = {}
+    for k in list(checkpoint.keys()):
+        if "llm_adapter" in k:
+            converted_state_dict[k.removeprefix("net.").removeprefix("model.diffusion_model.").removeprefix("llm_adapter.")] = checkpoint.pop(k)
+        else:
+            _ = checkpoint.pop(k)
+    return converted_state_dict
 
 def convert_cosmos_transformer_checkpoint_to_diffusers(checkpoint, **kwargs):
     converted_state_dict = {key: checkpoint.pop(key) for key in list(checkpoint.keys())}

src/diffusers/models/condition_embedders/condition_embedder_anima.py

@@ -17,7 +17,7 @@
 import torch.nn.functional as F
 
 from ...configuration_utils import ConfigMixin, register_to_config
-from ...loaders import PeftAdapterMixin
+from ...loaders import PeftAdapterMixin, FromOriginalModelMixin
 from ..attention import AttentionModuleMixin
 from ..attention_dispatch import dispatch_attention_fn
 from ..modeling_utils import ModelMixin
@@ -226,7 +226,7 @@ def forward(
         return hidden_states
 
 
-class AnimaTextConditioner(ModelMixin, ConfigMixin, PeftAdapterMixin):
+class AnimaTextConditioner(ModelMixin, ConfigMixin, FromOriginalModelMixin, PeftAdapterMixin):
     r"""
     Text conditioner used by Anima to map Qwen3 hidden states and T5 token ids to Cosmos text embeddings.