Update app.py

app.py

@@ -14,25 +14,12 @@ pipe = DiffusionPipeline.from_pretrained(
 pipe.load_lora_weights("Keltezaa/NSFW_MASTER_FLUX")
 pipe.to('cuda')
 
-compel = Compel(
-  tokenizer=[pipe.tokenizer, pipe.tokenizer_2] ,
-  text_encoder=[pipe.text_encoder, pipe.text_encoder_2],
-  returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED,
-  requires_pooled=[False, True]
-)
-
 
 @spaces.GPU(duration=120)
-def generate(prompt, negative_prompt, num_inference_steps, guidance_scale, width, height, num_samples):
-    embeds, pooled = compel(prompt)
-    neg_embeds, neg_pooled = compel(negative_prompt)
+def generate(prompt, num_inference_steps, width, height, num_samples):
     return pipe(
-        prompt_embeds=embeds,
-        pooled_prompt_embeds=pooled,
-        negative_prompt_embeds=neg_embeds,
-        negative_pooled_prompt_embeds=neg_pooled,
+        prompt,
         num_inference_steps=num_inference_steps,
-        guidance_scale=guidance_scale,
         width=width,
         height=height,
         num_images_per_prompt=num_samples
@@ -43,9 +30,7 @@ gr.Interface(
     fn=generate,
     inputs=[
         gr.Text(label="Prompt"),
-        gr.Text("", label="Negative Prompt"),
         gr.Number(7, label="Number inference steps"),
-        gr.Number(3, label="Guidance scale"),
         gr.Number(512, label="Width"),
         gr.Number(512, label="Height"),
         gr.Number(1, label="# images"),