Update app.py

app.py

@@ -8,22 +8,8 @@ hf_token = os.getenv("HF_TOKEN")
 model_id = int(os.getenv("Model"))
 nsfw_filter = int(os.getenv("Safe"))
 
-#stable-diffusion-xl-base-1.0  0 - base model
-#Colossus_Project_XL           1 - better people
-#AlbedoBaseXL_v11              2 - realistic
-#JuggernautXL_v7               3 - better faces
-#RealVisXL_V2.0                4 - better photorealism
-
-model_url_list = ["stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0.safetensors",
-                 "Krebzonide/Colossus_Project_XL/blob/main/colossusProjectXLSFW_v202BakedVAE.safetensors",
-                 "Krebzonide/AlbedoBaseXL_v11/blob/main/albedobaseXL_v11.safetensors",
-                 "Krebzonide/JuggernautXL_version5/blob/main/juggernautXL_v7Rundiffusion.safetensors",
-                 "SG161222/RealVisXL_V2.0/blob/main/RealVisXL_V2.0.safetensors",
-                 "Krebzonide/AcornIsSpinning_acornXLV1/blob/main/acornIsSpinning_acornxlV1.safetensors"]
-
 naughtyWords = ["nude", "nsfw", "naked", "porn", "boob", "tit", "nipple", "vagina", "pussy", "panties", "underwear", "upskirt", "bottomless", "topless", "petite", "xxx"]
 
-
 css = """
 .btn-green {
   background-image: linear-gradient(to bottom right, #6dd178, #00a613) !important;
@@ -56,10 +42,7 @@ def generate(prompt, samp_steps, batch_size, seed, progress=gr.Progress(track_tq
     ).images
     return gr.update(value = [(img, f"Image {i+1}") for i, img in enumerate(images)], height=height+90), seed
         
-def set_base_model(base_model_id):
-    vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-    global model_url_list
-    model_url = "https://huggingface.co/" + model_url_list[base_model_id]
+def set_base_model():
     pipe = AutoPipelineForText2Image.from_pretrained(
         "stabilityai/sdxl-turbo",
         torch_dtype = torch.float16,
@@ -81,5 +64,5 @@ with gr.Blocks(css=css) as demo:
         gallery = gr.Gallery(show_label=False, preview=True, container=False)
     submit_btn.click(generate, [prompt, samp_steps, batch_size, seed], [gallery, lastSeed], queue=True)
     
-pipe = set_base_model(model_id)
+pipe = set_base_model()
 demo.launch(debug=True)