FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style

Name: FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style
Author: Shakker-Labs

111

—

Shakker-Labs

Image Model

OTHER

New

111 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

Unknown

Mobile

Laptop

Server

Quick Summary

This is a flat cartoon style LoRA trained on FLUX.

Code Examples

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Showcasespythonpytorch

import torch
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image

pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-Kontext-dev-LoRA-Flat-Cartoon-Style", weight_name="FLUX-kontext-lora-flat-cartoon-style.safetensors")
pipe.fuse_lora(lora_scale=1.0)
pipe.to("cuda")

input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
prompt = "Convert to a flat cartoon style while keeping the subject unchanged"

image = pipe(
    image=input_image,
    prompt=prompt, 
    num_inference_steps=24, 
    guidance_scale=2.5,
).images[0]
image.save(f"example.png")

Deploy This Model

Production-ready deployment in minutes

Together.ai

Instant API access to this model

Fastest API

Production-ready inference API. Start free, scale to millions.

Try Free API

Replicate

One-click model deployment

Easiest Setup

Run models in the cloud with simple API. No DevOps required.

Deploy Now

Disclosure: We may earn a commission from these partners. This helps keep LLMYourWay free.