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docs/features/CLI.md
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@ -385,7 +385,7 @@ automatically.
Example:
<pre>
invoke> <b>!import_model models/ldm/stable-diffusion-v1/ model-epoch08-float16.ckpt</b>
invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b>
>> Model import in process. Please enter the values needed to configure this model:
Name for this model: <b>waifu-diffusion</b>

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docs/features/INSTALLING_MODELS.md
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@ -4,6 +4,258 @@ title: Installing Models
# :octicons-paintbrush-16: Installing Models
## TO COME
## Model Weight Files
The model weight files ('*.ckpt') are the Stable Diffusion "secret
sauce". They are the product of training the AI on millions of
captioned images gathered from multiple sources.
Originally there was only a single Stable Diffusion weights file,
which many people named `model.ckpt`. Now there are dozens or more
that have been "fine tuned" to provide particulary styles, genres, or
other features. InvokeAI allows you to install and run multiple model
weight files and switch between them quickly in the command-line and
web interfaces.
This manual will guide you through installing and configuring model
weight files.
## Base Models
InvokeAI comes with support for a good initial set of models listed in
the model configuration file `configs/models.yaml`. They are:
| Model | Weight File | Description | DOWNLOAD FROM |
| ---------------------- | ----------------------------- |--------------------------------- | ----------------|
| stable-diffusion-1.5 | v1-5-pruned-emaonly.ckpt | Most recent version of base Stable Diffusion model| https://huggingface.co/runwayml/stable-diffusion-v1-5 |
| stable-diffusion-1.4 | sd-v1-4.ckpt | Previous version of base Stable Diffusion model | https://huggingface.co/CompVis/stable-diffusion-v-1-4-original |
| inpainting-1.5 | sd-v1-5-inpainting.ckpt | Stable Diffusion 1.5 model specialized for inpainting | https://huggingface.co/runwayml/stable-diffusion-inpainting |
| waifu-diffusion-1.3 | model-epoch09-float32.ckpt | Stable Diffusion 1.4 trained to produce anime images | https://huggingface.co/hakurei/waifu-diffusion-v1-3 |
| <all models> | vae-ft-mse-840000-ema-pruned.ckpt | A fine-tune file add-on file that improves face generation | https://huggingface.co/stabilityai/sd-vae-ft-mse-original/ |
Note that these files are covered by an "Ethical AI" license which
forbids certain uses. You will need to create an account on the
Hugging Face website and accept the license terms before you can
access the files.
The predefined configuration file for InvokeAI (located at
`configs/models.yaml`) provides entries for each of these weights
files. `stable-diffusion-1.5` is the default model used, and we
strongly recommend that you install this weights file if nothing else.
## Community-Contributed Models
There are too many to list here and more are being contributed every
day. [This Page](https://rentry.org/sdmodels) hosts an updated list of
Stable Diffusion models and where they can be obtained.
## Installation
There are three ways to install weights files:
1. During InvokeAI installation, the `preload_models.py` script can
download them for you.
2. You can use the command-line interface (CLI) to import, configure
and modify new models files.
3. You can download the files manually and add the appropriate entries
to `models.yaml`.
### Installation via `preload_models.py`
This is the most automatic way. Run `scripts/preload_models.py` from
the console. It will ask you to select which models to download and
lead you through the steps of setting up a Hugging Face account if you
haven't done so already.
To start, from within the InvokeAI directory run the command `python
scripts/preload_models.py` (Linux/MacOS) or `python
scripts\preload_models.py` (Windows):
```
Loading Python libraries...
** INTRODUCTION **
Welcome to InvokeAI. This script will help download the Stable Diffusion weight files
and other large models that are needed for text to image generation. At any point you may interrupt
this program and resume later.
** WEIGHT SELECTION **
Would you like to download the Stable Diffusion model weights now? [y]
Choose the weight file(s) you wish to download. Before downloading you
will be given the option to view and change your selections.
[1] stable-diffusion-1.5:
The newest Stable Diffusion version 1.5 weight file (4.27 GB) (recommended)
Download? [y]
[2] inpainting-1.5:
RunwayML SD 1.5 model optimized for inpainting (4.27 GB) (recommended)
Download? [y]
[3] stable-diffusion-1.4:
The original Stable Diffusion version 1.4 weight file (4.27 GB)
Download? [n] n
[4] waifu-diffusion-1.3:
Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
Download? [n] y
[5] ft-mse-improved-autoencoder-840000:
StabilityAI improved autoencoder fine-tuned for human faces (recommended; 335 MB) (recommended)
Download? [y] y
The following weight files will be downloaded:
[1] stable-diffusion-1.5*
[2] inpainting-1.5
[4] waifu-diffusion-1.3
[5] ft-mse-improved-autoencoder-840000
*default
Ok to download? [y]
** LICENSE AGREEMENT FOR WEIGHT FILES **
1. To download the Stable Diffusion weight files you need to read and accept the
CreativeML Responsible AI license. If you have not already done so, please
create an account using the "Sign Up" button:
https://huggingface.co
You will need to verify your email address as part of the HuggingFace
registration process.
2. After creating the account, login under your account and accept
the license terms located here:
https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
Press <enter> when you are ready to continue:
...
```
When the script is complete, you will find the downloaded weights
files in `models/ldm/stable-diffusion-v1` and a matching configuration
file in `configs/models.yaml`.
You can run the script again to add any models you didn't select the
first time. Note that as a safety measure the script will _never_
remove a previously-installed weights file. You will have to do this
manually.
### Installation via the CLI
You can install a new model, including any of the community-supported
ones, via the command-line client's `!import_model` command.
1. First download the desired model weights file and place it under `models/ldm/stable-diffusion-v1/`.
You may rename the weights file to something more memorable if you wish. Record the path of the
weights file (e.g. `models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`)
2. Launch the `invoke.py` CLI with `python scripts/invoke.py`.
3. At the `invoke>` command-line, enter the command `!import_model <path to model>`.
For example:
`invoke> !import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`
(Hint - the CLI supports file path autocompletion. Type a bit of the path
name and hit <tab> in order to get a choice of possible completions.
4. Follow the wizard's instructions to complete installation as shown in the example
here:
```
invoke> <b>!import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt</b>
>> Model import in process. Please enter the values needed to configure this model:
Name for this model: <b>arabian-nights</b>
Description of this model: <b>Arabian Nights Fine Tune v1.0</b>
Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
Default image width: <b>512</b>
Default image height: <b>512</b>
>> New configuration:
arabian-nights:
config: configs/stable-diffusion/v1-inference.yaml
description: Arabian Nights Fine Tune v1.0
height: 512
weights: models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
width: 512
OK to import [n]? <b>y</b>
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
| LatentDiffusion: Running in eps-prediction mode
| DiffusionWrapper has 859.52 M params.
| Making attention of type 'vanilla' with 512 in_channels
| Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
| Making attention of type 'vanilla' with 512 in_channels
| Using faster float16 precision
```
If you've previously installed the fine-tune VAE file `vae-ft-mse-840000-ema-pruned.ckpt`,
the wizard will also ask you if you want to add this VAE to the model.
The appropriate entry for this model will be added to `configs/models.yaml` and it will
be available to use in the CLI immediately.
The CLI has additional commands for switching among, viewing, editing,
deleting the available models. These are described in [Command Line
Client](CLI.md#model-selection-and-importation), but the two most
frequently-used are `!models` and `!switch <name of model>`. The first
prints a table of models that InvokeAI knows about and their load
status. The second will load the requested model and lets you switch
back and forth quickly among loaded models.
### Manually editing of `configs/models.yaml`
If you are comfortable with a text editor then you may simply edit
`models.yaml` directly.
First you need to download the desired .ckpt file and place it in
`models/ldm/stable-diffusion-v1` as descirbed in step #1 in the
previous section. Record the path to the weights file,
e.g. `models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt`
Then using a **text** editor (e.g. the Windows Notepad application),
open the file `configs/models.yaml`, and add a new stanza that follows
this model:
```
arabian-nights-1.0:
description: A great fine-tune in Arabian Nights style
weights: ./models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
config: ./configs/stable-diffusion/v1-inference.yaml
width: 512
height: 512
vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
default: false
```
* arabian-nights-1.0
- This is the name of the model that you will refer to from within the
CLI and the WebGUI when you need to load and use the model.
* description
- Any description that you want to add to the model to remind you what
it is.
* weights
- Relative path to the .ckpt weights file for this model.
* config
- This is the confusingly-named configuration file for the model itself.
Use `./configs/stable-diffusion/v1-inference.yaml` unless the model happens
to need a custom configuration, in which case the place you downloaded it
from will tell you what to use instead. For example, the runwayML custom
inpainting model requires the file `configs/stable-diffusion/v1-inpainting-inference.yaml`.
(This is already inclued in the InvokeAI distribution and configured automatically
for you by the `preload_models.py` script.
* vae
- If you want to add a VAE file to the model, then enter its path here.
* width, height
- This is the width and height of the images used to train the model.
Currently they are always 512 and 512.
Save the `models.yaml` and relaunch InvokeAI. The new model should be
available for your use.

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@ -1,5 +1,5 @@
---
title: Linux
title: Manual Installation, Linux
---
# :fontawesome-brands-linux: Linux
@ -63,24 +63,16 @@ title: Linux
model loading scheme to allow the script to work on GPU machines that are not
internet connected. See [Preload Models](../features/OTHER.md#preload-models)
7. Now you need to install the weights for the stable diffusion model.
7. Install the weights for the stable diffusion model.
- For running with the released weights, you will first need to set up an acount
with [Hugging Face](https://huggingface.co).
- Use your credentials to log in, and then point your browser [here](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original).
- You may be asked to sign a license agreement at this point.
- Click on "Files and versions" near the top of the page, and then click on the
file named "sd-v1-4.ckpt". You'll be taken to a page that prompts you to click
the "download" link. Save the file somewhere safe on your local machine.
- Sign up at https://huggingface.co
- Go to the [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)
- Accept the terms and click Access Repository
- Download [v1-5-pruned-emaonly.ckpt (4.27 GB)](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt)
and move it into this directory under `models/ldm/stable_diffusion_v1/v1-5-pruned-emaonly.ckpt`
Now run the following commands from within the stable-diffusion directory.
This will create a symbolic link from the stable-diffusion model.ckpt file, to
the true location of the `sd-v1-4.ckpt` file.
```bash
(invokeai) ~/InvokeAI$ mkdir -p models/ldm/stable-diffusion-v1
(invokeai) ~/InvokeAI$ ln -sf /path/to/sd-v1-4.ckpt models/ldm/stable-diffusion-v1/model.ckpt
```
There are many other models that you can use. Please see [../features/INSTALLING_MODELS.md]
for details.
8. Start generating images!

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docs/installation/INSTALL_MAC.md
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@ -1,5 +1,5 @@
---
title: macOS
title: Manual Installation, macOS
---
# :fontawesome-brands-apple: macOS
@ -24,9 +24,15 @@ First you need to download a large checkpoint file.
1. Sign up at https://huggingface.co
2. Go to the [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)
3. Accept the terms and click Access Repository
4. Download [sd-v1-4.ckpt (4.27 GB)](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/blob/main/sd-v1-4.ckpt) and note where you have saved it (probably the Downloads folder). You may want to move it somewhere else for longer term storage - SD needs this file to run.
4. Download [v1-5-pruned-emaonly.ckpt (4.27 GB)](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt)
and move it into this directory under `models/ldm/stable_diffusion_v1/v1-5-pruned-emaonly.ckpt`
While that is downloading, open Terminal and run the following commands one at a time, reading the comments and taking care to run the appropriate command for your Mac's architecture (Intel or M1).
There are many other models that you can try. Please see [../features/INSTALLING_MODELS.md]
for details.
While that is downloading, open Terminal and run the following
commands one at a time, reading the comments and taking care to run
the appropriate command for your Mac's architecture (Intel or M1).
!!! todo "Homebrew"

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docs/installation/INSTALL_WINDOWS.md
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@ -1,5 +1,5 @@
---
title: Windows
title: Manual Installation, Windows
---
# :fontawesome-brands-windows: Windows
@ -83,23 +83,14 @@ in the wiki
8. Now you need to install the weights for the big stable diffusion model.
1. For running with the released weights, you will first need to set up an acount with Hugging Face (https://huggingface.co).
2. Use your credentials to log in, and then point your browser at https://huggingface.co/CompVis/stable-diffusion-v-1-4-original.
3. You may be asked to sign a license agreement at this point.
4. Click on "Files and versions" near the top of the page, and then click on the file named `sd-v1-4.ckpt`. You'll be taken to a page that
prompts you to click the "download" link. Now save the file somewhere safe on your local machine.
5. The weight file is >4 GB in size, so
downloading may take a while.
- Sign up at https://huggingface.co
- Go to the [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)
- Accept the terms and click Access Repository
- Download [v1-5-pruned-emaonly.ckpt (4.27 GB)](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt)
and move it into this directory under `models/ldm/stable_diffusion_v1/v1-5-pruned-emaonly.ckpt`
Now run the following commands from **within the InvokeAI directory** to copy the weights file to the right place:
```batch
mkdir -p models\ldm\stable-diffusion-v1
copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
```
Please replace `C:\path\to\sd-v1.4.ckpt` with the correct path to wherever you stashed this file. If you prefer not to copy or move the .ckpt file,
you may instead create a shortcut to it from within `models\ldm\stable-diffusion-v1\`.
There are many other models that you can use. Please see [../features/INSTALLING_MODELS.md]
for details.
9. Start generating images!

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ldm/invoke/model_cache.py
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@ -227,11 +227,14 @@ class ModelCache(object):
print(' | Using more accurate float32 precision')
# look and load a matching vae file. Code borrowed from AUTOMATIC1111 modules/sd_models.py
if vae and os.path.exists(vae):
print(f' | Loading VAE weights from: {vae}')
vae_ckpt = torch.load(vae, map_location="cpu")
vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
model.first_stage_model.load_state_dict(vae_dict, strict=False)
if vae:
if os.path.exists(vae):
print(f' | Loading VAE weights from: {vae}')
vae_ckpt = torch.load(vae, map_location="cpu")
vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
model.first_stage_model.load_state_dict(vae_dict, strict=False)
else:
print(f' | VAE file {vae} not found. Skipping.')
model.to(self.device)
# model.to doesn't change the cond_stage_model.device used to move the tokenizer output, so set it here

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models/ldm/stable-diffusion-v1/place-ckpt-files-here.txt Normal file
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@ -0,0 +1,2 @@
See docs/features/INSTALLING_MODELS.md for how to populate this
directory with one or more Stable Diffusion model weight files.