Instructions to use nitrosocke/Arcane-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Arcane-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/Arcane-Diffusion", 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
Onnx File Repo
#6
by averad - opened
Would it be possible to add an onnx branch?
Scripts:
https://github.com/huggingface/diffusers/blob/main/scripts/convert_original_stable_diffusion_to_diffusers.py
https://github.com/huggingface/diffusers/blob/main/scripts/convert_stable_diffusion_checkpoint_to_onnx.py
Compile:
python convert_original_stable_diffusion_to_diffusers.py --checkpoint_path="./arcane-diffusion-v3.ckpt" --dump_path="./arcane_diffusion_v3_diffusers"
python convert_stable_diffusion_checkpoint_to_onnx.py --model_path="./arcane_diffusion_v3_diffusers" --output_path="./arcane_diffusion_v3_onnx"
averad changed discussion status to closed
averad changed discussion status to open
Sure! I look into it
Added PR #20 with the Onnx Files.