diff --git a/extensions_built_in/diffusion_models/chroma/chroma_model.py b/extensions_built_in/diffusion_models/chroma/chroma_model.py
index 236d9508b..83ec1a669 100644
--- a/extensions_built_in/diffusion_models/chroma/chroma_model.py
+++ b/extensions_built_in/diffusion_models/chroma/chroma_model.py
@@ -167,8 +167,13 @@ def load_model(self):
 
         chroma_params.depth = double_blocks
         chroma_params.depth_single_blocks = single_blocks
+
+        # load Chroma into RAM in bfloat16, go back to fp32 afterwards
+        def_dtype = torch.get_default_dtype()
+        torch.set_default_dtype(torch.bfloat16)
         transformer = Chroma(chroma_params)
-        
+        torch.set_default_dtype(def_dtype)
+
         # add dtype, not sure why it doesnt have it
         transformer.dtype = dtype
         # load the state dict into the model
@@ -420,9 +425,13 @@ def get_model_has_grad(self):
         return self.model.final_layer.linear.weight.requires_grad
 
     def get_te_has_grad(self):
-        # return from a weight if it has grad
-        return self.text_encoder[1].encoder.block[0].layer[0].SelfAttention.q.weight.requires_grad
-    
+        from toolkit.unloader import FakeTextEncoder
+
+        te = self.text_encoder[1]
+        if isinstance(te, FakeTextEncoder):
+            return False
+        return te.encoder.block[0].layer[0].SelfAttention.q.weight.requires_grad
+
     def save_model(self, output_path, meta, save_dtype):
         if not output_path.endswith(".safetensors"):
             output_path =  output_path + ".safetensors"