Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import numpy as np
 import spaces
 import torch
-from diffusers import AutoPipelineForText2Image, AutoencoderKL  # , EulerDiscreteScheduler
+from diffusers import StableDiffusionXLPipeline, AutoencoderKL  # , EulerDiscreteScheduler
 
 # 添加导入语句
 from sd_embed.embedding_funcs import get_weighted_text_embeddings_sdxl
@@ -18,7 +18,7 @@ if torch.cuda.is_available():
     vae = AutoencoderKL.from_pretrained(
         "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
     )
-    pipe = AutoPipelineForText2Image.from_pretrained(
+    pipe = StableDiffusionXLPipeline.from_pretrained(
         "John6666/noobai-xl-nai-xl-epsilonpred075version-sdxl",
         vae=vae,
         torch_dtype=torch.float16,
@@ -38,7 +38,7 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 def infer(
     prompt: str,
     negative_prompt: str = "",
-    use_negative_prompt: bool = False,
+    use_negative_prompt: bool = True,
     seed: int = 1,
     width: int = 512,
     height: int = 768,
@@ -77,10 +77,10 @@ def infer(
         negative_pooled_prompt_embeds = None
 
     image = pipe(
-        prompt=prompt_embeds,
-        negative_prompt=prompt_neg_embeds,
-        #pooled_prompt_embeds=pooled_prompt_embeds,
-        #negative_pooled_prompt_embeds=negative_pooled_prompt_embeds,
+        prompt_embeds=prompt_embeds,
+        prompt_neg_embeds=prompt_neg_embeds,
+        pooled_prompt_embeds=pooled_prompt_embeds,
+        negative_pooled_prompt_embeds=negative_pooled_prompt_embeds,
         width=width,
         height=height,
         guidance_scale=guidance_scale,