Instructions to use Ling277/FaceComposer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ling277/FaceComposer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ling277/FaceComposer") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 868 Bytes
a9c9b18 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
base_model: black-forest-labs/FLUX.1-Fill-dev
instance_prompt: null
license: apache-2.0
---
# FaceComposer
<Gallery />
## Model description
Official research code for FaceComposer: Learning Coherent and Realistic Face Composition from References.
FaceComposer performs reference-based face composition: given a source portrait, a reference portrait, and selected facial components such as eyebrows, eyes, nose, or mouth, the model edits the source ROI toward the reference while preserving source pose, expression, illumination, and context.

## Download model
[Download](/Ling277/FaceComposer/tree/main) them in the Files & versions tab.
|