How to use HelloTestUser/FLUX.1-Fill-dev with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import FluxFillPipeline from diffusers.utils import load_image image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png") mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png") # switch to "mps" for apple devices pipe = FluxFillPipeline.from_pretrained("HelloTestUser/FLUX.1-Fill-dev", dtype=torch.bfloat16, device_map="cuda") image = pipe( prompt="a white paper cup", image=image, mask_image=mask, height=1632, width=1232, guidance_scale=30, num_inference_steps=50, max_sequence_length=512, generator=torch.Generator("cpu").manual_seed(0) ).images[0] image.save(f"flux-fill-dev.png")
How to use HelloTestUser/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
https://huggingface.co/HelloTestUser/FLUX.1-Fill-dev/resolve/main/tokenizer_2/tokenizer.json
hf download hf://HelloTestUser/FLUX.1-Fill-dev/tokenizer_2/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/HelloTestUser/FLUX.1-Fill-dev/resolve/main/tokenizer_2/tokenizer.json
