diff --git a/src/diffusers/loaders/single_file_model.py b/src/diffusers/loaders/single_file_model.py
index 610e377d3ab9..3545fa7598ba 100644
--- a/src/diffusers/loaders/single_file_model.py
+++ b/src/diffusers/loaders/single_file_model.py
@@ -31,6 +31,7 @@
 from ..utils.torch_utils import empty_device_cache
 from .single_file_utils import (
     SingleFileComponentError,
+    convert_anima_text_conditioner_to_diffusers,
     convert_animatediff_checkpoint_to_diffusers,
     convert_auraflow_transformer_checkpoint_to_diffusers,
     convert_autoencoder_dc_checkpoint_to_diffusers,
@@ -193,6 +194,10 @@
         "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",
diff --git a/src/diffusers/loaders/single_file_utils.py b/src/diffusers/loaders/single_file_utils.py
index e65e0be50f62..26005552e387 100644
--- a/src/diffusers/loaders/single_file_utils.py
+++ b/src/diffusers/loaders/single_file_utils.py
@@ -3736,6 +3736,22 @@ def swap_scale_shift(weight):
     return converted_state_dict
 
 
+def convert_anima_text_conditioner_to_diffusers(checkpoint, **kwargs):
+    # If none of the keys has the `llm_adapter` prefix, we assume it is a diffusers-format file 
+    # containing ONLY the text conditioner weights and nothing else
+    has_prefix = any(key.startswith("llm_adapter") for key in checkpoint.keys())
+    if not has_prefix: 
+        return checkpoint
+    
+    converted_state_dict = {}
+    for k in list(checkpoint.keys()):
+        if "llm_adapter." in k:
+            converted_state_dict[k.split("llm_adapter.", 1)[1]] = 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())}
 
diff --git a/src/diffusers/models/condition_embedders/condition_embedder_anima.py b/src/diffusers/models/condition_embedders/condition_embedder_anima.py
index 40fda447ec68..65ab281d9317 100644
--- a/src/diffusers/models/condition_embedders/condition_embedder_anima.py
+++ b/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 FromOriginalModelMixin, PeftAdapterMixin
 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.