2.2 KiB
Stable-Diffusion-Burn
Stable-Diffusion-Burn is a Rust-based project which ports the V1 stable diffusion model into the deep learning framework, Burn. This repository is licensed under the MIT Licence.
How To Use
Step 1: Download the Model and Set Environment Variables
Start by downloading the SDv1-4.bin model provided on HuggingFace.
wget https://huggingface.co/Gadersd/Stable-Diffusion-Burn/resolve/main/V1/SDv1-4.bin
Next, set the appropriate CUDA version.
export TORCH_CUDA_VERSION=cu113
Step 2: Run the Sample Binary
Invoke the sample binary provided in the rust code, as shown below. Loading the burn model file is currently very slow, but hopefully that will be rectified soon. You can also dump a torch model's weights and load that which is currently much faster.
# Arguments: <model_type(burn or dump)> <model> <unconditional_guidance_scale> <n_diffusion_steps> <prompt> <output_image>
cargo run --release --bin sample burn SDv1-4 7.5 20 "A half-eaten apple sitting on a desk." apple
This command will generate an image according to the provided prompt, which will be saved as 'apple.png'.
Optional: Extract and Convert a Fine-Tuned Model
If users are interested in using a fine-tuned version of stable diffusion, the Python scripts provided in this project can be used to transform a weight dump into a Burn model file.
# Step into the Python directory
cd python
# Download the model, this is just the base v1.4 model as an example
wget https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
# Extract the weights
python3 dump.py sd-v1-4.ckpt
# Move the extracted weight folder out
mv params ..
# Step out of the Python directory
cd ..
# Convert the weights into a usable form
cargo run --release --bin convert params SDv1-4
The binaries 'convert' and 'sample' are contained in Rust. Convert works on CPU whereas sample needs CUDA.
Remember, convert should be used if you're planning on using the fine-tuned version of the stable diffusion.
License
This project is licensed under MIT license.
Example Inference
INSER IMAGE HERE
We wish you a productive time using this project. Enjoy!