Instructions to use xinsir/controlnet-union-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xinsir/controlnet-union-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
key errors when loading weights
#25
by minhaohan2 - opened
initializing the controlnet model in diffusers through the following call
controlnet = diffusers.ControlNetModel.from_pretrained(
"xinsir/controlnet-union-sdxl-1.0", # regular
torch_dtype=torch.float16,
use_safetensors = True
)
results in the following warning:
Some weights of the model checkpoint were not used when initializing ControlNetModel:
['control_add_embedding.linear_1.bias, control_add_embedding.linear_1.weight, control_add_embedding.linear_2.bias, control_add_embedding.linear_2.weight, spatial_ch_projs.bias, spatial_ch_projs.weight, task_embedding, transformer_layes.0.attn.in_proj_bias, transformer_layes.0.attn.in_proj_weight, transformer_layes.0.attn.out_proj.bias, transformer_layes.0.attn.out_proj.weight, transformer_layes.0.ln_1.bias, transformer_layes.0.ln_1.weight, transformer_layes.0.ln_2.bias, transformer_layes.0.ln_2.weight, transformer_layes.0.mlp.c_fc.bias, transformer_layes.0.mlp.c_fc.weight, transformer_layes.0.mlp.c_proj.bias, transformer_layes.0.mlp.c_proj.weight']
wondering if this impacts performance, or can be safely ignored.