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)

```python
from diffusers import AutoPipelineForText2Image
import torch

# 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')

# Define different aspect ratios
aspect_ratios = [
    (512, 512),  # 1:1
    (768, 768),  # 3:3 (same as 1:1 but larger)
    (640, 512),  # 5:4
    (768, 512),  # 3:2
    (896, 512),  # 7:4
]

# Generate images for each aspect ratio
for width, height in aspect_ratios:
    image = pipeline(
        'tugce in a beautiful garden',
        width=width,
        height=height
    ).images[0]
    
    # Save the image
    image.save(f"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)