Instructions to use black-forest-labs/FLUX.1-Fill-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use black-forest-labs/FLUX.1-Fill-dev 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") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use black-forest-labs/FLUX.1-Fill-dev with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
object-removal?
#13
by Clement - opened
Is it possible to perform object removal with this model just by tweaking the inference params (I couldn't make it work so far), or would this task require fine-tuning?
Clement changed discussion title from object-removal to object-removal?
Also curious
You can use segmentation tool like SAM to create a mask of the object you want to remove and then fill it with FLUX.