changed the model to mem-token

app.py

@@ -17,11 +17,11 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=dtype).to(device)
 pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=vae).to(device)
-pipe.load_lora_weights("azad-uddin/crypto-token-azad", weight_name="crypto-token-azad.safetensors")
+pipe.load_lora_weights("azad-uddin/meme-token", weight_name="meme-token.safetensors")
 torch.cuda.empty_cache()
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 512
+MAX_IMAGE_SIZE = 1024
 
 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
 
@@ -33,7 +33,7 @@ def infer(prompt, seed=42, randomize_seed=False, width=512, height=512, guidance
     
     final_img = None
     for img in pipe.flux_pipe_call_that_returns_an_iterable_of_images(
-            prompt= f"{prompt}. crYpt0 azad",
+            prompt= f"memestylx, {prompt}, all within a circular emblem",
             guidance_scale=guidance_scale,
             num_inference_steps=num_inference_steps,
             width=width,
@@ -45,8 +45,8 @@ def infer(prompt, seed=42, randomize_seed=False, width=512, height=512, guidance
         final_img = img
     
     if final_img is not None:
-        with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp_file:
-            final_img.save(tmp_file.name, format="JPEG")
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp_file:
+            final_img.save(tmp_file.name, format="PNG")
             image_path = tmp_file.name
             return image_path
     return None