Update README.md

README.md

@@ -12,38 +12,33 @@ base_model: "black-forest-labs/FLUX.1-dev"
 pipeline_tag: text-to-image
 instance_prompt: DHANUSH
 ---
-
 # Tugce_Flux
-
 Trained on Replicate using:
-
 https://replicate.com/ostris/flux-dev-lora-trainer/train
 
-
 ## Trigger words
 You should use `tugce` to trigger the image generation.
 
-
 ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
 
-```py
+```python
 from diffusers import AutoPipelineForText2Image
 import torch
 
-# Model ve LoRA'yı yükle
+# Load the model and LoRA weights
 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')
 
-# Farklı en boy oranları
+# Define different aspect ratios
 aspect_ratios = [
     (512, 512),  # 1:1
-    (768, 768),  # 3:3 (aslında 1:1 ile aynı oran)
+    (768, 768),  # 3:3 (same as 1:1 but larger)
     (640, 512),  # 5:4
     (768, 512),  # 3:2
     (896, 512),  # 7:4
 ]
 
-# Her bir oran için görüntü oluştur
+# Generate images for each aspect ratio
 for width, height in aspect_ratios:
     image = pipeline(
         'tugce in a beautiful garden',
@@ -51,9 +46,13 @@ for width, height in aspect_ratios:
         height=height
     ).images[0]
     
-    # Görüntüyü kaydet
+    # Save the image
     image.save(f"tugce_{width}x{height}.png")
-    print(f"Oluşturuldu: tugce_{width}x{height}.png")
+    print(f"Generated: tugce_{width}x{height}.png")
 ```
 
+This code will generate images in various aspect ratios. You can modify the `aspect_ratios` list to include any desired dimensions.
+
+Remember to use the trigger word `tugce` in your prompts to activate the LoRA model.
+
 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)