Update README.md

README.md

@@ -35,37 +35,28 @@ You should use `TOK` to trigger the image generation.
 ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
 
 ```py
-from diffusers import AutoPipelineForText2Image, AutoencoderKL
+from diffusers import AutoPipelineForText2Image
 import torch
 
-# 1. Ana modeli yükle
+# 1. Realistic Vision modelini yükle
 pipeline = AutoPipelineForText2Image.from_pretrained(
     "SG161222/Realistic_Vision_V6.0_B1_noVAE",
-    torch_dtype=torch.float16,
-    variant="fp16"
-).to("cuda")
-
-# 2. VAE ekle (opsiyonel)
-pipeline.vae = AutoencoderKL.from_pretrained(
-    "stabilityai/sd-vae-ft-mse",
     torch_dtype=torch.float16
 ).to("cuda")
 
-# 3. LoRA'yı yükle
+# 2. LoRA'yı zorla yükle (alpha=0.5 ile gücünü azaltın)
 pipeline.load_lora_weights(
     "codermert/gamzekocc_fluxx",
     weight_name="lora.safetensors",
-    adapter_name="fluxx_style"
+    adapter_name="fluxx",
+    cross_attention_scale=0.5  # LoRA etkisini hafiflet
 )
 
-# 4. Görüntü oluştur
+# 3. Promptta hem trigger hem stil vurgusu yapın
 image = pipeline(
-    prompt="portrait of a cyber ninja, <fluxx_style>, ultra-detailed, 8K",
-    negative_prompt="blurry, cartoon, deformed",
-    num_inference_steps=30
+    prompt="portrait of TOK, <fluxx>, photorealistic, 8K",  # TOK + adapter_name
+    negative_prompt="blurry, deformed"
 ).images[0]
-
-image.save("cyber_ninja.png")
 ```
 
 For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)