import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-Children-Simple-Sketch")
prompt = "sketched style,A stick-figure-style robot, and some sci-fi machines, with pastel colors, highlight the innocence and romance of children"
image = pipe(prompt).images[0]FLUX.1-dev-LoRA-Children-Simple-Sketch
This is a LoRA trained on FLUX.1-dev for Children's Simple-Sketch by Hongke on Shakker AI.
Showcases
- Prompt
- sketched style,A stick-figure-style robot, and some sci-fi machines, with pastel colors, highlight the innocence and romance of children
- Prompt
- sketched style,A joyful girl with balloons floats above a city wearing a hat and striped pants,
- Prompt
- sketched style,Some happy children stand ready to take pictures
Trigger words
You should use sketched style to trigger the image generation. The recommended scale is 0.8 to 1.5 in diffusers.
Inference
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-Children-Simple-Sketch", weight_name="FLUX-dev-lora-children-simple-sketch.safetensors")
pipe.fuse_lora(lora_scale=1.5)
pipe.to("cuda")
prompt = "sketched style,A joyful girl with balloons floats above a city wearing a hat and striped pants,"
image = pipe(prompt,
num_inference_steps=24,
guidance_scale=3.5,
).images[0]
image.save(f"example.png")
Online Inference
You can also run this model at Shakker AI, where we provide an online interface to generate images.
Acknowledgements
This model is trained by our copyrighted users Hongke. We release this model under permissions. The model follows flux-1-dev-non-commercial-license.
- Downloads last month
- 340
Model tree for Shakker-Labs/FLUX.1-dev-LoRA-Children-Simple-Sketch
Base model
black-forest-labs/FLUX.1-dev