Update app.py

app.py

@@ -28,16 +28,19 @@ torch.backends.cuda.matmul.allow_tf32 = True
 
 pipe = FluxPipeline.from_pretrained("AlekseyCalvin/HistoricColorSoonr_v2_FluxSchnell_Diffusers", ignore_mismatched_sizes=True, torch_dtype=torch.bfloat16)
 pipe.to(device="cuda", dtype=torch.bfloat16)
-clipmodel = 'long' # 'norm', 'long' (my fine-tunes) - 'oai', 'orgL' (OpenAI / BeichenZhang original)
-selectedprompt = 'long' # 'tiny' (51 tokens), 'short' (75), 'med' (116), 'long' (203)
+clipmodel = 'norm' # 'norm', 'long' (my fine-tunes) - 'oai', 'orgL' (OpenAI / BeichenZhang original)
 
 if clipmodel == "long":
     model_id = "zer0int/LongCLIP-GmP-ViT-L-14"
     config = CLIPConfig.from_pretrained(model_id)
-    maxtokens = 248
+    maxtokens = 77
+if clipmodel == "norm":
+    model_id = "zer0int/CLIP-GmP-ViT-L-14"
+    config = CLIPConfig.from_pretrained(model_id)
+    maxtokens = 77
 clip_model = CLIPModel.from_pretrained(model_id, torch_dtype=torch.bfloat16, config=config, ignore_mismatched_sizes=True).to("cuda")
 clip_processor = CLIPProcessor.from_pretrained(model_id, padding="max_length", max_length=maxtokens, ignore_mismatched_sizes=True, return_tensors="pt", truncation=True)
-config.text_config.max_position_embeddings = 248
+config.text_config.max_position_embeddings = 77
 
 pipe.tokenizer = clip_processor.tokenizer
 pipe.text_encoder = clip_model.text_model
@@ -189,17 +192,17 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
         with gr.Accordion("Advanced Settings", open=True):
             with gr.Column():
                 with gr.Row():
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=1.0)
+                    cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=0.5, value=0.5)
                     steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=6)
                 
                 with gr.Row():
-                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=768)
+                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
                     height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
                 
                 with gr.Row():
                     randomize_seed = gr.Checkbox(True, label="Randomize seed")
                     seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
-                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=2.0, step=0.01, value=0.6)
+                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=2.0, step=0.01, value=0.9)
 
     gallery.select(
         update_selection,