README.md

---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
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
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')

# Farklı boyutlar
sizes = [
    (512, 512),  # 1:1
    (768, 512),  # 3:2
    (640, 480),  # 4:3
    (896, 504),  # 16:9
]

# Prompt
prompt = "tugce in a beautiful garden"

# Her boyut için görüntü oluştur
for width, height in sizes:
    image = pipeline(
        prompt,
        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)