Instructions to use prithivMLmods/QIE-2511-Cinematic-FlatLog-Control with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prithivMLmods/QIE-2511-Cinematic-FlatLog-Control with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("prithivMLmods/QIE-2511-Cinematic-FlatLog-Control") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("prithivMLmods/QIE-2511-Cinematic-FlatLog-Control")
prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]QIE-2511-Cinematic-FlatLog-Control
QIE-2511-Cinematic-FlatLog-Control is an adapter LoRA developed for Qwenβs Qwen-Image-Edit-2511 image-to-image model, designed to transform images into a cinematic flat log look. The model reduces contrast and saturation to achieve a neutral, log-style tonal response while preserving the original identity, composition, textures, and geometry. It enables consistent cinematic grading workflows with smooth highlight roll-off, controlled shadows, and artifact-free results.
Quick Start with Diffusers
Compatible with versions 2509 and 2511.
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# Switch to "mps" for Apple devices
pipe = DiffusionPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit-2511",
dtype=torch.bfloat16,
device_map="cuda"
)
pipe.load_lora_weights("prithivMLmods/QIE-2511-Cinematic-FlatLog-Control")
prompt = "Transform into a cinematic flat log"
input_image = load_image(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png"
)
image = pipe(image=input_image, prompt=prompt).images[0]
Trained on ModelScope.cn
Trigger Prompt
Use the following prompt to activate the cinematic flat log behavior:
Transform into a cinematic flat log
Download Model
You can download the model files from the Files & versions tab: Download
@misc{prithiv_sakthi_2026,
author = { Prithiv Sakthi },
title = { QIE-2511-Cinematic-FlatLog-Control (Revision 6498672) },
year = 2026,
url = { https://huggingface.co/prithivMLmods/QIE-2511-Cinematic-FlatLog-Control },
doi = { 10.57967/hf/7732 },
publisher = { Hugging Face }
}
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Model tree for prithivMLmods/QIE-2511-Cinematic-FlatLog-Control
Base model
Qwen/Qwen-Image-Edit-2511
