Ben_Kosytorz/stable-diffusion-burn-vibe
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Update to burn v0.14.0 and switch to .mpk model file

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2024-10-05 14:19:49 -04:00
parent 9e4d7bd310
commit 893fb0950d
19 changed files with 366 additions and 311 deletions
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README.md
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@@ -4,12 +4,14 @@ Stable-Diffusion-Burn is a Rust-based project which ports the V1 stable diffusio
## How To Use
### Step 0: Install libtorch v2.4.1
### Step 1: Download the Model and Set Environment Variables
Start by downloading the SDv1-4.bin model provided on HuggingFace.
Start by downloading the SDv1-4 model provided on HuggingFace.
```bash
wget https://huggingface.co/Gadersd/Stable-Diffusion-Burn/resolve/main/V1/SDv1-4.bin
wget https://huggingface.co/Gadersd/Stable-Diffusion-Burn/resolve/main/SDv1-4.mpk
```
### Step 2: Run the Sample Binary
@@ -18,9 +20,13 @@ Invoke the sample binary provided in the rust code. By default, torch is used. T
```bash
# torch (at least 6 GB VRAM, possibly less)
export TORCH_CUDA_VERSION=cu113
# 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 "An ancient mossy stone." img
# Arguments: <model_type(burn or dump)> <model_name> <unconditional_guidance_scale> <n_diffusion_steps> <prompt> <output_image_name> [cuda, mps, cpu]
# Cuda
cargo run --release --bin sample burn SDv1-4 7.5 20 "An ancient mossy stone." img cuda
# Mps(Mac)
cargo run --release --bin sample burn SDv1-4 7.5 20 "An ancient mossy stone." img mps
# wgpu (UNSTABLE)
# Arguments: <model_type(burn or dump)> <model> <unconditional_guidance_scale> <n_diffusion_steps> <prompt> <output_image>
@@ -33,7 +39,7 @@ This command will generate an image according to the provided prompt, which will
### 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. Note: the tinygrad dependency should be installed from source rather than with pip.
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. This does not work on Windows.
```bash
# Step into the Python directory
@@ -42,6 +48,9 @@ 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
# Install tinygrad
pip install -r requirements.txt
# Extract the weights
CPU=1 python3 dump.py sd-v1-4.ckpt