Update app.py

app.py

@@ -4,9 +4,9 @@ import gradio as gr
 import torch
 import numpy as np
 import random
-from diffusers import FluxPipeline, FluxTransformer2DModel
-import transformers
+from diffusers import FluxPipeline
 from translatepy import Translator
+from huggingface_hub import hf_hub_download
 
 
 os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
@@ -29,13 +29,11 @@ JS = """function () {
   }
 }"""
 
-transformer = FluxTransformer2DModel.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16)
-
 if torch.cuda.is_available():
-    pipe = FluxPipeline.from_pretrained(
-        model,
-        transformer=transformer,
-        torch_dtype=torch.bfloat16).to("cuda")
+    pipe = FluxPipeline.from_pretrained(model, torch_dtype=torch.bfloat16)
+    pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"))
+    pipe.fuse_lora(lora_scale=0.125)
+    pipe.to(device="cuda", dtype=torch.bfloat16)
 
 # Function 
 @spaces.GPU(duration=120)
@@ -93,7 +91,7 @@ examples = [
 
 with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
     gr.HTML("<h1><center>Flux Labs</center></h1>")
-    gr.HTML("<p><center>Model Now: <a href='https://huggingface.co/sayakpaul/FLUX.1-merged'>FLUX.1 Merged</a><br>🙇‍♂️Frequent model changes</center></p>")
+    gr.HTML("<p><center>Model Now:  Hyper-FLUX-8steps-LoRA<br>🙇‍♂️Frequent model changes</center></p>")
     with gr.Row():
         with gr.Column(scale=4):
             img = gr.Gallery(label='flux Generated Image', columns = 1, preview=True, height=600)