Update app.py

app.py

@@ -129,7 +129,14 @@ Elaborate on each core requirement to create a rich description.
         model_inputs = QWEN_TOKENIZER([text], return_tensors="pt").to(QWEN_MODEL.device)
         
         with torch.no_grad():
-            generated_ids = QWEN_MODEL.generate(**model_inputs, max_new_tokens=4096, temperature=0.6)
+            generated_ids = QWEN_MODEL.generate(
+                **model_inputs,
+                max_new_tokens=512,          # ← 从 4096 改成 512 够用
+                temperature=0.6,
+                top_p=0.9,
+                do_sample=True,
+                eos_token_id=QWEN_TOKENIZER.eos_token_id,
+            )
         
         output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
         full_response = QWEN_TOKENIZER.decode(output_ids, skip_special_tokens=True)
@@ -254,11 +261,14 @@ def create_interface():
                 )
                 
                 with gr.Row():
-                    width_input = gr.Slider(label="宽度", minimum=256, maximum=MAX_IMAGE_SIZE, value=768, step=32)
-                    height_input = gr.Slider(label="高度", minimum=256, maximum=MAX_IMAGE_SIZE, value=1024, step=32)
+                    # 默认宽度 832，高度 1216
+                    width_input = gr.Slider(label="宽度", minimum=256, maximum=MAX_IMAGE_SIZE, value=832, step=32)
+                    height_input = gr.Slider(label="高度", minimum=256, maximum=MAX_IMAGE_SIZE, value=1216, step=32)
                 
-                num_inference_steps_input = gr.Slider(label="推理步数", minimum=1, maximum=100, value=20, step=1)
-                guidance_scale_input = gr.Slider(label="引导强度", minimum=0.0, maximum=20.0, value=3.5, step=0.1)
+                # 默认步数 28
+                num_inference_steps_input = gr.Slider(label="推理步数", minimum=1, maximum=100, value=28, step=1)
+                # 默认 CFG 28，为了能取到 28，将最大值提高到 40
+                guidance_scale_input = gr.Slider(label="引导强度", minimum=0.0, maximum=40.0, value=28, step=0.1)
                 seed_number_input = gr.Number(label="种子 (-1 随机)", value=-1, minimum=-1, step=1)
                 generate_button = gr.Button("🎨 生成海报", variant="primary", size="lg")