Instructions to use alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Beta 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("alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Beta", dtype=torch.bfloat16, device_map="cuda") 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] - Notebooks
- Google Colab
- Kaggle
File size: 524 Bytes
411df28 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"_class_name": "FluxControlNetModel",
"_diffusers_version": "0.30.2",
"_name_or_path": "/data/oss_bucket_0/linjinpeng.ljp/exp_flux/r768_bs96_adamw_lr5e-6_bf16_cfg3.5_sin0_dou6_s11/checkpoint-50000",
"attention_head_dim": 128,
"axes_dims_rope": [
16,
56,
56
],
"extra_condition_channels": 4,
"guidance_embeds": true,
"in_channels": 64,
"joint_attention_dim": 4096,
"num_attention_heads": 24,
"num_layers": 6,
"num_single_layers": 0,
"patch_size": 1,
"pooled_projection_dim": 768
}
|