---
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- image-generation
- flux
- safetensors
widget:
- text: >-
A young man, gold hair, white T-shirt. The background is 4 real photos, and
in the middle is a cartoon picture summarizing the real photos.
output:
url: images/b4425607370dcaa80717519f157a64436dd92238dc60786639845551.jpg
- text: >-
A panda.The background is 4 real photos, and in the middle is a cartoon
picture summarizing the real photos.
output:
url: images/f2cc649985648e57b9b9b14ca7a8744ac8e50d75b3a334ed4df0f368.jpg
- text: >-
A young girl, red hair, blue dress. The background is 4 real photos, and in
the middle is a cartoon picture summarizing the real photos.
output:
url: images/9104a1e9c1debdb1188c06a5e07bf4a084f0d8005e082f01f8de7c19.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: >-
The background is 4 real photos, and in the middle is a cartoon picture
summarizing the real photos
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
library_name: diffusers
---
# FLUX.1-dev-LoRA-One-Click-Creative-Template
This is a LoRA trained on FLUX.1-dev by [Nvwa_model_studio](https://www.shakker.ai/userpage/cd65d71ff6a74bbfaaeba0b898dbf856/publish) for creative photos.
## Showcases
## Trigger words
You should use `The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos.` to trigger the image generation. The recommended scale is `1.0` in diffusers.
## Inference
```python
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-One-Click-Creative-Template", weight_name="FLUX-dev-lora-One-Click-Creative-Template.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")
prompt = "A young girl, red hair, blue dress. The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos."
image = pipe(prompt,
num_inference_steps=24,
guidance_scale=3.5,
width=960, height=1280,
).images[0]
image.save(f"example.png")
```
## Online Inference
You can also download this model at [Shakker AI](https://www.shakker.ai/modelinfo/16681dcf76e7447a83731c02eb4f4efe?from=personal_page), where we provide an online interface to generate images.
We also provide an [online ComfyUI workflow](https://www.shakker.ai/modelinfo/c81474e2a6fc40cb9c26a7f4a3b7d691/Generate-interesting-sticker-avatars-with-one-click?from=search) (Click Run Model) that accepts user-uploaded images to generate images
## Acknowledgements
This model is trained by our copyrighted users [Nvwa_model_studio](https://www.shakker.ai/userpage/cd65d71ff6a74bbfaaeba0b898dbf856/publish). We release this model under permissions.