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---
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) |