update INSTALLING_MODELS.md

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@ -6,81 +6,77 @@ title: Installing Models
## 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.
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.
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.
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:
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/ |
| `<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.
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.
`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. Hugging Face maintains a [fast-growing
repository](https://huggingface.co/sd-concepts-library) of fine-tune
(".bin") models that can be imported into InvokeAI by passing the
There are too many to list here and more are being contributed every day.
Hugging Face maintains a
[fast-growing repository](https://huggingface.co/sd-concepts-library) of
fine-tune (".bin") models that can be imported into InvokeAI by passing the
`--embedding_path` option to the `invoke.py` command.
[This page](https://rentry.org/sdmodels) hosts a large list of
official and unofficial Stable Diffusion models and where they can be
obtained.
[This page](https://rentry.org/sdmodels) hosts a large list of official and
unofficial 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.
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.
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`.
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.
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):
To start, run `python scripts/preload_models.py` from within the InvokeAI:
directory
```
!!! example ""
```text
Loading Python libraries...
** INTRODUCTION **
@ -136,46 +132,50 @@ 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`.
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.
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.
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`)
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:
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.)
!!! tip "the CLI supports file path autocompletion"
4. Follow the wizard's instructions to complete installation as shown in the example
here:
Type a bit of the path name and hit ++tab++ in order to get a choice of
possible completions.
```
invoke> <b>!import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt</b>
4. Follow the wizard's instructions to complete installation as shown in the
example here:
!!! example ""
```text
invoke> !import_model models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
>> 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>
Name for this model: arabian-nights
Description of this model: Arabian Nights Fine Tune v1.0
Configuration file for this model: configs/stable-diffusion/v1-inference.yaml
Default image width: 512
Default image height: 512
>> New configuration:
arabian-nights:
config: configs/stable-diffusion/v1-inference.yaml
@ -183,7 +183,7 @@ arabian-nights:
height: 512
weights: models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
width: 512
OK to import [n]? <b>y</b>
OK to import [n]? y
>> 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
@ -192,38 +192,37 @@ OK to import [n]? <b>y</b>
| 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.
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 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](../features/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.
The CLI has additional commands for switching among, viewing, editing, deleting
the available models. These are described in
[Command Line Client](../features/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.
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`
`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:
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:
```
```yaml
arabian-nights-1.0:
description: A great fine-tune in Arabian Nights style
weights: ./models/ldm/stable-diffusion-v1/arabian-nights-1.0.ckpt
@ -234,34 +233,14 @@ arabian-nights-1.0:
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 is 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.
| name | description |
| :----------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 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 is 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 now be
available for your use.