Cleanup some lumina te code.

comfy/text_encoders/lumina2.py

@@ -19,11 +19,6 @@ def __init__(self, embedding_directory=None, tokenizer_data={}):
 
 class Gemma2_2BModel(sd1_clip.SDClipModel):
     def __init__(self, device="cpu", layer="hidden", layer_idx=-2, dtype=None, attention_mask=True, model_options={}):
-        llama_scaled_fp8 = model_options.get("llama_scaled_fp8", None)
-        if llama_scaled_fp8 is not None:
-            model_options = model_options.copy()
-            model_options["scaled_fp8"] = llama_scaled_fp8
-
         super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"start": 2, "pad": 0}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Gemma2_2B, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
 
 
@@ -35,10 +30,10 @@ def __init__(self, device="cpu", dtype=None, model_options={}):
 def te(dtype_llama=None, llama_scaled_fp8=None):
     class LuminaTEModel_(LuminaModel):
         def __init__(self, device="cpu", dtype=None, model_options={}):
-            if llama_scaled_fp8 is not None and "llama_scaled_fp8" not in model_options:
+            if llama_scaled_fp8 is not None and "scaled_fp8" not in model_options:
                 model_options = model_options.copy()
-                model_options["llama_scaled_fp8"] = llama_scaled_fp8
-                if dtype_llama is not None:
-                    dtype = dtype_llama
+                model_options["scaled_fp8"] = llama_scaled_fp8
+            if dtype_llama is not None:
+                dtype = dtype_llama
             super().__init__(device=device, dtype=dtype, model_options=model_options)
     return LuminaTEModel_