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@ -116,20 +116,25 @@ git clone https://github.com/lstein/stable-diffusion.git
```
This will create stable-diffusion folder where you will follow the rest of the steps.
6. Run the following two commands:
6. Enter the newly-created stable-diffusion folder. From this step forward make sure that you are working in the stable-diffusion directory!
```
conda env create -f environment.yaml
conda activate ldm
cd stable-diffusion
```
This will install all python requirements (step 6a) and activate the "ldm" environment which sets PATH and other environment variables properly (6b).
7. Run the command:
7. Run the following two commands:
```
conda env create -f environment.yaml (step 7a)
conda activate ldm (step 7b)
```
This will install all python requirements and activate the "ldm" environment which sets PATH and other environment variables properly.
8. Run the command:
```
python scripts/preload_models.py
```
This installs two machine learning models that stable diffusion requires.
8. Now you need to install the weights for the big stable diffusion model.
9. Now you need to install the weights for the big stable diffusion model.
For testing prior to the release of the real weights, create a directory within stable-diffusion named "models\ldm\text2img.large"
```
@ -142,7 +147,7 @@ mkdir models\ldm\stable-diffusion-v1
```
Then use a web browser to copy model.ckpt into the appropriate directory. For the text2img.large (pre-release) model, the weights are at https://ommer-lab.com/files/latent-diffusion/nitro/txt2img-f8-large/model.ckpt
9. Generate your first image:
10. Generate your first image:
```
# for the pre-release weights
python scripts\dream.py -l
@ -150,7 +155,7 @@ python scripts\dream.py -l
# for the post-release weights
python scripts\dream.py
```
10. Subsequently, to relaunch the script, first activate the Anaconda command window (step 4), run "conda activate ldm" (step 6b), and then launch the dream script (step 9).
11. Subsequently, to relaunch the script, first activate the Anaconda command window (step 4), run "conda activate ldm" (step 7b), and then launch the dream script (step 10).
### Updating to newer versions of the script