Update app.py

app.py

@@ -21,7 +21,6 @@ from transformers import T5EncoderModel, T5Tokenizer
 from transformers import pipeline, AutoTokenizer, MarianMTModel
 
 
-
 class HFEmbedder(nn.Module):
     def __init__(self, version: str, max_length: int, **hf_kwargs):
         super().__init__()
@@ -55,7 +54,6 @@ class HFEmbedder(nn.Module):
             output_hidden_states=False,
         )
         return outputs[self.output_key]
-    
 
 device = "cuda"
 t5 = HFEmbedder("DeepFloyd/t5-v1_1-xxl", max_length=512, torch_dtype=torch.bfloat16).to(device)
@@ -65,9 +63,6 @@ ae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="va
 # freeze(t5)
 
 
-# ---------------- NF4 ----------------
-
-
 def functional_linear_4bits(x, weight, bias):
     out = bnb.matmul_4bit(x, weight.t(), bias=bias, quant_state=weight.quant_state)
     out = out.to(x)
@@ -205,9 +200,6 @@ class Linear(ForgeLoader4Bit):
 nn.Linear = Linear
 
 
-# ---------------- Model ----------------
-
-
 def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor) -> Tensor:
     q, k = apply_rope(q, k, pe)
 
@@ -732,8 +724,6 @@ def get_image(image) -> torch.Tensor | None:
     return img[None, ...]
 
 
-# ---------------- Demo ----------------
-
 
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
@@ -744,9 +734,6 @@ model = Flux().to(dtype=torch.bfloat16, device="cuda")
 result = model.load_state_dict(sd)
 model_zero_init = False
 
-# model = Flux().to(dtype=torch.bfloat16, device="cuda")
-# result = model.load_state_dict(load_file("/storage/dev/nyanko/flux-dev/flux1-dev.sft"))
-
 
 # 언어-모델 매핑 딕셔너리 추가
 TRANSLATORS = {
@@ -926,6 +913,8 @@ footer {
 
 def create_demo():
     with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css) as demo:
+    gr.Markdown("# FLUXllama Multilingual(36 Languages")  
+    
         with gr.Row():
             with gr.Column():
                 source_lang = gr.Dropdown(