Update README.md

README.md

@@ -30,9 +30,30 @@ You should use `tugce` to trigger the image generation.
 from diffusers import AutoPipelineForText2Image
 import torch
 
+# Model ve LoRA'yı yükle
 pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
 pipeline.load_lora_weights('codermert/tugce2-lora', weight_name='flux_train_replicate.safetensors')
-image = pipeline('your prompt').images[0]
+
+# Farklı en boy oranları
+aspect_ratios = [
+    (512, 512),  # 1:1
+    (768, 768),  # 3:3 (aslında 1:1 ile aynı oran)
+    (640, 512),  # 5:4
+    (768, 512),  # 3:2
+    (896, 512),  # 7:4
+]
+
+# Her bir oran için görüntü oluştur
+for width, height in aspect_ratios:
+    image = pipeline(
+        'tugce in a beautiful garden',
+        width=width,
+        height=height
+    ).images[0]
+    
+    # Görüntüyü kaydet
+    image.save(f"tugce_{width}x{height}.png")
+    print(f"Oluşturuldu: tugce_{width}x{height}.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)