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---
title: build binary installers
---
# :simple-buildkite: How to build "binary" installers (InvokeAI-mac/windows/linux_on_*.zip)
## 1. Ensure `installers/requirements.in` is correct
and up to date on the branch to be installed.
## <a name="step-2"></a> 2. Run `pip-compile` on each platform.
On each target platform, in the branch that is to be installed, and
inside the InvokeAI git root folder, run the following commands:
```commandline
conda activate invokeai # or however you activate python
pip install pip-tools
pip-compile --allow-unsafe --generate-hashes --output-file=binary_installer/<reqsfile>.txt binary_installer/requirements.in
```
where `<reqsfile>.txt` is whichever of
```commandline
py3.10-darwin-arm64-mps-reqs.txt
py3.10-darwin-x86_64-reqs.txt
py3.10-linux-x86_64-cuda-reqs.txt
py3.10-windows-x86_64-cuda-reqs.txt
```
matches the current OS and architecture.
> There is no way to cross-compile these. They must be done on a system matching the target OS and arch.
## <a name="step-3"></a> 3. Set github repository and branch
Once all reqs files have been collected and committed **to the branch
to be installed**, edit `binary_installer/install.sh.in` and `binary_installer/install.bat.in` so that `RELEASE_URL`
and `RELEASE_SOURCEBALL` point to the github repo and branch that is
to be installed.
For example, to install `main` branch of `InvokeAI`, they should be
set as follows:
`install.sh.in`:
```commandline
RELEASE_URL=https://github.com/invoke-ai/InvokeAI
RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
```
`install.bat.in`:
```commandline
set RELEASE_URL=https://github.com/invoke-ai/InvokeAI
set RELEASE_SOURCEBALL=/archive/refs/heads/main.tar.gz
```
Or, to install `damians-cool-feature` branch of `damian0815`, set them
as follows:
`install.sh.in`:
```commandline
RELEASE_URL=https://github.com/damian0815/InvokeAI
RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
```
`install.bat.in`:
```commandline
set RELEASE_URL=https://github.com/damian0815/InvokeAI
set RELEASE_SOURCEBALL=/archive/refs/heads/damians-cool-feature.tar.gz
```
The branch and repo specified here **must** contain the correct reqs
files. The installer zip files **do not** contain requirements files,
they are pulled from the specified branch during the installation
process.
## 4. Create zip files.
cd into the `installers/` folder and run
`./create_installers.sh`. This will create
`InvokeAI-mac_on_<branch>.zip`,
`InvokeAI-windows_on_<branch>.zip` and
`InvokeAI-linux_on_<branch>.zip`. These files can be distributed to end users.
These zips will continue to function as installers for all future
pushes to those branches, as long as necessary changes to
`requirements.in` are propagated in a timely manner to the
`py3.10-*-reqs.txt` files using pip-compile as outlined in [step
2](#step-2).
To actually install, users should unzip the appropriate zip file into an empty
folder and run `install.sh` on macOS/Linux or `install.bat` on
Windows.

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---
title: InvokeAI Binary Installer
---
The InvokeAI binary installer is a shell script that will install InvokeAI onto a stock
computer running recent versions of Linux, MacOSX or Windows. It will leave you
with a version that runs a stable version of InvokeAI. When a new version of
InvokeAI is released, you will download and reinstall the new version.
If you wish to tinker with unreleased versions of InvokeAI that introduce
potentially unstable new features, you should consider using the
[source installer](INSTALL_SOURCE.md) or one of the
[manual install](../020_INSTALL_MANUAL.md) methods.
**Important Caveats**
- This script does not support AMD GPUs. For Linux AMD support,
please use the manual or source code installer methods.
- This script has difficulty on some Macintosh machines
that have previously been used for Python development due to
conflicting development tools versions. Mac developers may wish
to try the source code installer or one of the manual methods instead.
!!! todo
Before you begin, make sure that you meet
the[hardware requirements](/#hardware-requirements) and has the
appropriate GPU drivers installed. In particular, if you are a Linux user with
an AMD GPU installed, you may need to install the
[ROCm-driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
Installation requires roughly 18G of free disk space to load the libraries and
recommended model weights files.
## Steps to Install
1. Download the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) of
InvokeAI's installer for your platform. Look for a file named `InvokeAI-binary-<your platform>.zip`
2. Place the downloaded package someplace where you have plenty of HDD space,
and have full permissions (i.e. `~/` on Lin/Mac; your home folder on Windows)
3. Extract the 'InvokeAI' folder from the downloaded package
4. Open the extracted 'InvokeAI' folder
5. Double-click 'install.bat' (Windows), or 'install.sh' (Lin/Mac) (or run from
a terminal)
6. Follow the prompts
7. After installation, please run the 'invoke.bat' file (on Windows) or
'invoke.sh' file (on Linux/Mac) to start InvokeAI.
## Troubleshooting
If you run into problems during or after installation, the InvokeAI team is
available to help you. Either create an
[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
make a request for help on the "bugs-and-support" channel of our
[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
organization, but typically somebody will be available to help you within 24
hours, and often much sooner.

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---
title: Running InvokeAI on Google Colab using a Jupyter Notebook
---
## Introduction
We have a [Jupyter
notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
with cell-by-cell installation steps. It will download the code in
this repo as one of the steps, so instead of cloning this repo, simply
download the notebook from the link above and load it up in VSCode
(with the appropriate extensions installed)/Jupyter/JupyterLab and
start running the cells one-by-one.
!!! Note "you will need NVIDIA drivers, Python 3.10, and Git installed beforehand"
## Running Online On Google Colabotary
[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
## Running Locally (Cloning)
1. Install the Jupyter Notebook python library (one-time):
pip install jupyter
2. Clone the InvokeAI repository:
git clone https://github.com/invoke-ai/InvokeAI.git
cd invoke-ai
3. Create a virtual environment using conda:
conda create -n invoke jupyter
4. Activate the environment and start the Jupyter notebook:
conda activate invoke
jupyter notebook

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---
title: Manual Installation, Linux
---
# :fontawesome-brands-linux: Linux
## Installation
1. You will need to install the following prerequisites if they are not already
available. Use your operating system's preferred installer.
- Python (version 3.8.5 recommended; higher may work)
- git
2. Install the Python Anaconda environment manager.
```bash
~$ wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
~$ chmod +x Anaconda3-2022.05-Linux-x86_64.sh
~$ ./Anaconda3-2022.05-Linux-x86_64.sh
```
After installing anaconda, you should log out of your system and log back
in. If the installation worked, your command prompt will be prefixed by the
name of the current anaconda environment - `(base)`.
3. Copy the InvokeAI source code from GitHub:
```bash
(base) ~$ git clone https://github.com/invoke-ai/InvokeAI.git
```
This will create InvokeAI folder where you will follow the rest of the
steps.
4. Enter the newly-created InvokeAI folder. From this step forward make sure
that you are working in the InvokeAI directory!
```bash
(base) ~$ cd InvokeAI
(base) ~/InvokeAI$
```
5. Use anaconda to copy necessary python packages, create a new python
environment named `invokeai` and then activate the environment.
!!! todo "For systems with a CUDA (Nvidia) card:"
```bash
(base) rm -rf src # (this is a precaution in case there is already a src directory)
(base) ~/InvokeAI$ conda env create -f environment-cuda.yml
(base) ~/InvokeAI$ conda activate invokeai
(invokeai) ~/InvokeAI$
```
!!! todo "For systems with an AMD card (using ROCm driver):"
```bash
(base) rm -rf src # (this is a precaution in case there is already a src directory)
(base) ~/InvokeAI$ conda env create -f environment-AMD.yml
(base) ~/InvokeAI$ conda activate invokeai
(invokeai) ~/InvokeAI$
```
After these steps, your command prompt will be prefixed by `(invokeai)` as
shown above.
6. Load the big stable diffusion weights files and a couple of smaller
machine-learning models:
```bash
(invokeai) ~/InvokeAI$ python3 scripts/configure_invokeai.py
```
!!! note
This script will lead you through the process of creating an account on Hugging Face,
accepting the terms and conditions of the Stable Diffusion model license,
and obtaining an access token for downloading. It will then download and
install the weights files for you.
Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing
the same thing.
7. Start generating images!
!!! todo "Run InvokeAI!"
!!! warning "IMPORTANT"
Make sure that the conda environment is activated, which should create
`(invokeai)` in front of your prompt!
=== "CLI"
```bash
python scripts/invoke.py
```
=== "local Webserver"
```bash
python scripts/invoke.py --web
```
=== "Public Webserver"
```bash
python scripts/invoke.py --web --host 0.0.0.0
```
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
8. Subsequently, to relaunch the script, be sure to run "conda activate
invokeai" (step 5, second command), enter the `InvokeAI` directory, and then
launch the invoke script (step 8). If you forget to activate the 'invokeai'
environment, the script will fail with multiple `ModuleNotFound` errors.
## Updating to newer versions of the script
This distribution is changing rapidly. If you used the `git clone` method
(step 5) to download the InvokeAI directory, then to update to the latest and
greatest version, launch the Anaconda window, enter `InvokeAI` and type:
```bash
(invokeai) ~/InvokeAI$ git pull
(invokeai) ~/InvokeAI$ rm -rf src # prevents conda freezing errors
(invokeai) ~/InvokeAI$ conda env update -f environment.yml
```
This will bring your local copy into sync with the remote one.

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---
title: Manual Installation, macOS
---
# :fontawesome-brands-apple: macOS
Invoke AI runs quite well on M1 Macs and we have a number of M1 users in the
community.
While the repo does run on Intel Macs, we only have a couple reports. If you
have an Intel Mac and run into issues, please create an issue on Github and we
will do our best to help.
## Requirements
- macOS 12.3 Monterey or later
- About 10GB of storage (and 10GB of data if your internet connection has data
caps)
- Any M1 Macs or an Intel Macs with 4GB+ of VRAM (ideally more)
## Installation
!!! todo "Homebrew"
First you will install the "brew" package manager. Skip this if brew is already installed.
```bash title="install brew (and Xcode command line tools)"
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
```
!!! todo "Conda Installation"
Now there are two different ways to set up the Python (miniconda) environment:
1. Standalone
2. with pyenv
If you don't know what we are talking about, choose Standalone. If you are familiar with python environments, choose "with pyenv"
=== "Standalone"
```bash title="Install cmake, protobuf, and rust"
brew install cmake protobuf rust
```
```bash title="Clone the InvokeAI repository"
# Clone the Invoke AI repo
git clone https://github.com/invoke-ai/InvokeAI.git
cd InvokeAI
```
Choose the appropriate architecture for your system and install miniconda:
=== "M1 arm64"
```bash title="Install miniconda for M1 arm64"
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh \
-o Miniconda3-latest-MacOSX-arm64.sh
/bin/bash Miniconda3-latest-MacOSX-arm64.sh
```
=== "Intel x86_64"
```bash title="Install miniconda for Intel"
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh \
-o Miniconda3-latest-MacOSX-x86_64.sh
/bin/bash Miniconda3-latest-MacOSX-x86_64.sh
```
=== "with pyenv"
```bash
brew install pyenv-virtualenv
pyenv install anaconda3-2022.05
pyenv virtualenv anaconda3-2022.05
eval "$(pyenv init -)"
pyenv activate anaconda3-2022.05
```
!!! todo "Clone the Invoke AI repo"
```bash
git clone https://github.com/invoke-ai/InvokeAI.git
cd InvokeAI
```
!!! todo "Create the environment & install packages"
=== "M1 Mac"
```bash
PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac.yml
```
=== "Intel x86_64 Mac"
```bash
PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-64 conda env create -f environment-mac.yml
```
```bash
# Activate the environment (you need to do this every time you want to run SD)
conda activate invokeai
```
!!! info
`export PIP_EXISTS_ACTION=w` is a precaution to fix `conda env
create -f environment-mac.yml` never finishing in some situations. So
it isn't required but won't hurt.
!!! todo "Download the model weight files"
The `configure_invokeai.py` script downloads and installs the model weight
files for you. It will lead you through the process of getting a Hugging Face
account, accepting the Stable Diffusion model weight license agreement, and
creating a download token:
```bash
# This will take some time, depending on the speed of your internet connection
# and will consume about 10GB of space
python scripts/configure_invokeai.py
```
!!! todo "Run InvokeAI!"
!!! warning "IMPORTANT"
Make sure that the conda environment is activated, which should create
`(invokeai)` in front of your prompt!
=== "CLI"
```bash
python scripts/invoke.py
```
=== "local Webserver"
```bash
python scripts/invoke.py --web
```
=== "Public Webserver"
```bash
python scripts/invoke.py --web --host 0.0.0.0
```
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
---
## Common problems
After you followed all the instructions and try to run invoke.py, you might get
several errors. Here's the errors I've seen and found solutions for.
### Is it slow?
```bash title="Be sure to specify 1 sample and 1 iteration."
python ./scripts/orig_scripts/txt2img.py \
--prompt "ocean" \
--ddim_steps 5 \
--n_samples 1 \
--n_iter 1
```
---
### Doesn't work anymore?
PyTorch nightly includes support for MPS. Because of this, this setup is
inherently unstable. One morning I woke up and it no longer worked no matter
what I did until I switched to miniforge. However, I have another Mac that works
just fine with Anaconda. If you can't get it to work, please search a little
first because many of the errors will get posted and solved. If you can't find a
solution please [create an issue](https://github.com/invoke-ai/InvokeAI/issues).
One debugging step is to update to the latest version of PyTorch nightly.
```bash
conda install \
pytorch \
torchvision \
-c pytorch-nightly \
-n invokeai
```
If it takes forever to run `conda env create -f environment-mac.yml`, try this:
```bash
git clean -f
conda clean \
--yes \
--all
```
Or you could try to completley reset Anaconda:
```bash
conda update \
--force-reinstall \
-y \
-n base \
-c defaults conda
```
---
### "No module named cv2", torch, 'invokeai', 'transformers', 'taming', etc
There are several causes of these errors:
1. Did you remember to `conda activate invokeai`? If your terminal prompt begins
with "(invokeai)" then you activated it. If it begins with "(base)" or
something else you haven't.
2. You might've run `./scripts/configure_invokeai.py` or `./scripts/invoke.py`
instead of `python ./scripts/configure_invokeai.py` or
`python ./scripts/invoke.py`. The cause of this error is long so it's below.
<!-- I could not find out where the error is, otherwise would have marked it as a footnote -->
3. if it says you're missing taming you need to rebuild your virtual
environment.
```bash
conda deactivate
conda env remove -n invokeai
conda env create -f environment-mac.yml
```
4. If you have activated the invokeai virtual environment and tried rebuilding
it, maybe the problem could be that I have something installed that you don't
and you'll just need to manually install it. Make sure you activate the
virtual environment so it installs there instead of globally.
```bash
conda activate invokeai
pip install <package name>
```
You might also need to install Rust (I mention this again below).
---
### How many snakes are living in your computer?
You might have multiple Python installations on your system, in which case it's
important to be explicit and consistent about which one to use for a given
project. This is because virtual environments are coupled to the Python that
created it (and all the associated 'system-level' modules).
When you run `python` or `python3`, your shell searches the colon-delimited
locations in the `PATH` environment variable (`echo $PATH` to see that list) in
that order - first match wins. You can ask for the location of the first
`python3` found in your `PATH` with the `which` command like this:
```bash
% which python3
/usr/bin/python3
```
Anything in `/usr/bin` is
[part of the OS](https://developer.apple.com/library/archive/documentation/FileManagement/Conceptual/FileSystemProgrammingGuide/FileSystemOverview/FileSystemOverview.html#//apple_ref/doc/uid/TP40010672-CH2-SW6).
However, `/usr/bin/python3` is not actually python3, but rather a stub that
offers to install Xcode (which includes python 3). If you have Xcode installed
already, `/usr/bin/python3` will execute
`/Library/Developer/CommandLineTools/usr/bin/python3` or
`/Applications/Xcode.app/Contents/Developer/usr/bin/python3` (depending on which
Xcode you've selected with `xcode-select`).
Note that `/usr/bin/python` is an entirely different python - specifically,
python 2. Note: starting in macOS 12.3, `/usr/bin/python` no longer exists.
```bash
% which python3
/opt/homebrew/bin/python3
```
If you installed python3 with Homebrew and you've modified your path to search
for Homebrew binaries before system ones, you'll see the above path.
```bash
% which python
/opt/anaconda3/bin/python
```
If you have Anaconda installed, you will see the above path. There is a
`/opt/anaconda3/bin/python3` also.
We expect that `/opt/anaconda3/bin/python` and `/opt/anaconda3/bin/python3`
should actually be the _same python_, which you can verify by comparing the
output of `python3 -V` and `python -V`.
```bash
(invokeai) % which python
/Users/name/miniforge3/envs/invokeai/bin/python
```
The above is what you'll see if you have miniforge and correctly activated the
invokeai environment, while usingd the standalone setup instructions above.
If you otherwise installed via pyenv, you will get this result:
```bash
(anaconda3-2022.05) % which python
/Users/name/.pyenv/shims/python
```
It's all a mess and you should know
[how to modify the path environment variable](https://support.apple.com/guide/terminal/use-environment-variables-apd382cc5fa-4f58-4449-b20a-41c53c006f8f/mac)
if you want to fix it. Here's a brief hint of the most common ways you can
modify it (don't really have the time to explain it all here).
- ~/.zshrc
- ~/.bash_profile
- ~/.bashrc
- /etc/paths.d
- /etc/path
Which one you use will depend on what you have installed, except putting a file
in /etc/paths.d - which also is the way I prefer to do.
Finally, to answer the question posed by this section's title, it may help to
list all of the `python` / `python3` things found in `$PATH` instead of just the
first hit. To do so, add the `-a` switch to `which`:
```bash
% which -a python3
...
```
This will show a list of all binaries which are actually available in your PATH.
---
### Debugging?
Tired of waiting for your renders to finish before you can see if it works?
Reduce the steps! The image quality will be horrible but at least you'll get
quick feedback.
```bash
python ./scripts/txt2img.py \
--prompt "ocean" \
--ddim_steps 5 \
--n_samples 1 \
--n_iter 1
```
---
### OSError: Can't load tokenizer for 'openai/clip-vit-large-patch14'
```bash
python scripts/configure_invokeai.py
```
---
### "The operator [name] is not current implemented for the MPS device." (sic)
!!! example "example error"
```bash
... NotImplementedError: The operator 'aten::_index_put_impl_' is not current
implemented for the MPS device. If you want this op to be added in priority
during the prototype phase of this feature, please comment on
https://github.com/pytorch/pytorch/issues/77764.
As a temporary fix, you can set the environment variable
`PYTORCH_ENABLE_MPS_FALLBACK=1` to use the CPU as a fallback for this op.
WARNING: this will be slower than running natively on MPS.
```
The InvokeAI version includes this fix in
[environment-mac.yml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yml).
### "Could not build wheels for tokenizers"
I have not seen this error because I had Rust installed on my computer before I
started playing with Stable Diffusion. The fix is to install Rust.
```bash
curl \
--proto '=https' \
--tlsv1.2 \
-sSf https://sh.rustup.rs | sh
```
---
### How come `--seed` doesn't work?
!!! Information
Completely reproducible results are not guaranteed across PyTorch releases,
individual commits, or different platforms. Furthermore, results may not be
reproducible between CPU and GPU executions, even when using identical seeds.
[PyTorch docs](https://pytorch.org/docs/stable/notes/randomness.html)
Second, we might have a fix that at least gets a consistent seed sort of. We're
still working on it.
### libiomp5.dylib error?
```bash
OMP: Error #15: Initializing libiomp5.dylib, but found libomp.dylib already initialized.
```
You are likely using an Intel package by mistake. Be sure to run conda with the
environment variable `CONDA_SUBDIR=osx-arm64`, like so:
`CONDA_SUBDIR=osx-arm64 conda install ...`
This error happens with Anaconda on Macs when the Intel-only `mkl` is pulled in
by a dependency.
[nomkl](https://stackoverflow.com/questions/66224879/what-is-the-nomkl-python-package-used-for)
is a metapackage designed to prevent this, by making it impossible to install
`mkl`, but if your environment is already broken it may not work.
Do _not_ use `os.environ['KMP_DUPLICATE_LIB_OK']='True'` or equivalents as this
masks the underlying issue of using Intel packages.
---
### Not enough memory
This seems to be a common problem and is probably the underlying problem for a
lot of symptoms (listed below). The fix is to lower your image size or to add
`model.half()` right after the model is loaded. I should probably test it out.
I've read that the reason this fixes problems is because it converts the model
from 32-bit to 16-bit and that leaves more RAM for other things. I have no idea
how that would affect the quality of the images though.
See [this issue](https://github.com/CompVis/stable-diffusion/issues/71).
---
### "Error: product of dimension sizes > 2\*\*31'"
This error happens with img2img, which I haven't played with too much yet. But I
know it's because your image is too big or the resolution isn't a multiple of
32x32. Because the stable-diffusion model was trained on images that were 512 x
512, it's always best to use that output size (which is the default). However,
if you're using that size and you get the above error, try 256 x 256 or 512 x
256 or something as the source image.
BTW, 2\*\*31-1 =
[2,147,483,647](https://en.wikipedia.org/wiki/2,147,483,647#In_computing), which
is also 32-bit signed [LONG_MAX](https://en.wikipedia.org/wiki/C_data_types) in
C.
---
### I just got Rickrolled! Do I have a virus?
You don't have a virus. It's part of the project. Here's
[Rick](https://github.com/invoke-ai/InvokeAI/blob/main/assets/rick.jpeg) and
here's
[the code](https://github.com/invoke-ai/InvokeAI/blob/69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc/scripts/txt2img.py#L79)
that swaps him in. It's a NSFW filter, which IMO, doesn't work very good (and we
call this "computer vision", sheesh).
---
### My images come out black
We might have this fixed, we are still testing.
There's a [similar issue](https://github.com/CompVis/stable-diffusion/issues/69)
on CUDA GPU's where the images come out green. Maybe it's the same issue?
Someone in that issue says to use "--precision full", but this fork actually
disables that flag. I don't know why, someone else provided that code and I
don't know what it does. Maybe the `model.half()` suggestion above would fix
this issue too. I should probably test it.
### "view size is not compatible with input tensor's size and stride"
```bash
File "/opt/anaconda3/envs/invokeai/lib/python3.10/site-packages/torch/nn/functional.py", line 2511, in layer_norm
return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.
```
Update to the latest version of invoke-ai/InvokeAI. We were patching pytorch but
we found a file in stable-diffusion that we could change instead. This is a
32-bit vs 16-bit problem.
### The processor must support the Intel bla bla bla
What? Intel? On an Apple Silicon?
```bash
Intel MKL FATAL ERROR: This system does not meet the minimum requirements for use of the Intel(R) Math Kernel Library. The processor must support the Intel(R) Supplemental Streaming SIMD Extensions 3 (Intel(R) SSSE3) instructions. The processor must support the Intel(R) Streaming SIMD Extensions 4.2 (Intel(R) SSE4.2) instructions. The processor must support the Intel(R) Advanced Vector Extensions (Intel(R) AVX) instructions.
```
This is due to the Intel `mkl` package getting picked up when you try to install
something that depends on it-- Rosetta can translate some Intel instructions but
not the specialized ones here. To avoid this, make sure to use the environment
variable `CONDA_SUBDIR=osx-arm64`, which restricts the Conda environment to only
use ARM packages, and use `nomkl` as described above.
---
### input types 'tensor<2x1280xf32>' and 'tensor<\*xf16>' are not broadcast compatible
May appear when just starting to generate, e.g.:
```bash
invoke> clouds
Generating: 0%| | 0/1 [00:00<?, ?it/s]/Users/[...]/dev/stable-diffusion/ldm/modules/embedding_manager.py:152: UserWarning: The operator 'aten::nonzero' is not currently supported on the MPS backend and will fall back to run on the CPU. This may have performance implications. (Triggered internally at /Users/runner/work/_temp/anaconda/conda-bld/pytorch_1662016319283/work/aten/src/ATen/mps/MPSFallback.mm:11.)
placeholder_idx = torch.where(
loc("mps_add"("(mpsFileLoc): /AppleInternal/Library/BuildRoots/20d6c351-ee94-11ec-bcaf-7247572f23b4/Library/Caches/com.apple.xbs/Sources/MetalPerformanceShadersGraph/mpsgraph/MetalPerformanceShadersGraph/Core/Files/MPSGraphUtilities.mm":219:0)): error: input types 'tensor<2x1280xf32>' and 'tensor<*xf16>' are not broadcast compatible
LLVM ERROR: Failed to infer result type(s).
Abort trap: 6
/Users/[...]/opt/anaconda3/envs/invokeai/lib/python3.9/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
```

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@ -1,17 +0,0 @@
---
title: Installing InvokeAI with the Pre-Compiled PIP Installer
---
# THIS NEEDS TO BE FLESHED OUT
## Introduction
## Walkthrough
## Updating to newer versions
### Updating the stable version
### Updating to the development version
## Troubleshooting

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---
title: Source Installer
---
# The InvokeAI Source Installer
## Introduction
The source installer is a shell script that attempts to automate every step
needed to install and run InvokeAI on a stock computer running recent versions
of Linux, MacOS or Windows. It will leave you with a version that runs a stable
version of InvokeAI with the option to upgrade to experimental versions later.
Before you begin, make sure that you meet the
[hardware requirements](../../index.md#hardware-requirements) and has the appropriate
GPU drivers installed. In particular, if you are a Linux user with an AMD GPU
installed, you may need to install the
[ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
Installation requires roughly 18G of free disk space to load the libraries and
recommended model weights files.
## Walk through
Though there are multiple steps, there really is only one click involved to kick
off the process.
1. The source installer is distributed in ZIP files. Go to the
[latest release](https://github.com/invoke-ai/InvokeAI/releases/latest), and
look for a series of files named:
- [invokeAI-src-installer-2.2.3-mac.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-mac.zip)
- [invokeAI-src-installer-2.2.3-windows.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-windows.zip)
- [invokeAI-src-installer-2.2.3-linux.zip](https://github.com/invoke-ai/InvokeAI/releases/latest/download/invokeAI-src-installer-2.2.3-linux.zip)
Download the one that is appropriate for your operating system.
2. Unpack the zip file into a directory that has at least 18G of free space. Do
_not_ unpack into a directory that has an earlier version of InvokeAI.
This will create a new directory named "InvokeAI". This example shows how
this would look using the `unzip` command-line tool, but you may use any
graphical or command-line Zip extractor:
```cmd
C:\Documents\Linco> unzip invokeAI-windows.zip
Archive: C: \Linco\Downloads\invokeAI-linux.zip
creating: invokeAI\
inflating: invokeAI\install.bat
inflating: invokeAI\readme.txt
```
3. If you are a macOS user, you may need to install the Xcode command line tools.
These are a set of tools that are needed to run certain applications in a Terminal,
including InvokeAI. This package is provided directly by Apple.
To install, open a terminal window and run `xcode-select --install`. You will get
a macOS system popup guiding you through the install. If you already have them
installed, you will instead see some output in the Terminal advising you that the
tools are already installed.
More information can be found here:
https://www.freecodecamp.org/news/install-xcode-command-line-tools/
4. If you are using a desktop GUI, double-click the installer file. It will be
named `install.bat` on Windows systems and `install.sh` on Linux and
Macintosh systems.
5. Alternatively, from the command line, run the shell script or .bat file:
```cmd
C:\Documents\Linco> cd invokeAI
C:\Documents\Linco\invokeAI> install.bat
```
6. Sit back and let the install script work. It will install various binary
requirements including Conda, Git and Python, then download the current
InvokeAI code and install it along with its dependencies.
Be aware that some of the library download and install steps take a long time.
In particular, the `pytorch` package is quite large and often appears to get
"stuck" at 99.9%. Similarly, the `pip installing requirements` step may
appear to hang. Have patience and the installation step will eventually
resume. However, there are occasions when the library install does
legitimately get stuck. If you have been waiting for more than ten minutes
and nothing is happening, you can interrupt the script with ^C. You may restart
it and it will pick up where it left off.
7. After installation completes, the installer will launch a script called
`configure_invokeai.py`, which will guide you through the first-time process of
selecting one or more Stable Diffusion model weights files, downloading and
configuring them.
Note that the main Stable Diffusion weights file is protected by a license
agreement that you must agree to in order to use. The script will list the
steps you need to take to create an account on the official site that hosts
the weights files, accept the agreement, and provide an access token that
allows InvokeAI to legally download and install the weights files.
If you have already downloaded the weights file(s) for another Stable
Diffusion distribution, you may skip this step (by selecting "skip" when
prompted) and configure InvokeAI to use the previously-downloaded files. The
process for this is described in [Installing Models](../050_INSTALLING_MODELS.md).
8. The script will now exit and you'll be ready to generate some images. The
invokeAI directory will contain numerous files. Look for a shell script
named `invoke.sh` (Linux/Mac) or `invoke.bat` (Windows). Launch the script
by double-clicking it or typing its name at the command-line:
```cmd
C:\Documents\Linco> cd invokeAI
C:\Documents\Linco\invokeAI> invoke.bat
```
The `invoke.bat` (`invoke.sh`) script will give you the choice of starting (1)
the command-line interface, or (2) the web GUI. If you start the latter, you can
load the user interface by pointing your browser at http://localhost:9090.
The `invoke` script also offers you a third option labeled "open the developer
console". If you choose this option, you will be dropped into a command-line
interface in which you can run python commands directly, access developer tools,
and launch InvokeAI with customized options. To do the latter, you would launch
the script `scripts/invoke.py` as shown in this example:
```cmd
python scripts/invoke.py --web --max_load_models=3 \
--model=waifu-1.3 --steps=30 --outdir=C:/Documents/AIPhotos
```
These options are described in detail in the
[Command-Line Interface](../../deprecated/CLI.md) documentation.
## Troubleshooting
_Package dependency conflicts_ If you have previously installed
InvokeAI or another Stable Diffusion package, the installer may
occasionally pick up outdated libraries and either the installer or
`invoke` will fail with complaints out library conflicts. There are
two steps you can take to clear this problem. Both of these are done
from within the "developer's console", which you can get to by
launching `invoke.sh` (or `invoke.bat`) and selecting launch option
#3:
1. Remove the previous `invokeai` environment completely. From within
the developer's console, give the command `conda env remove -n
invokeai`. This will delete previous files installed by `invoke`.
Then exit from the developer's console and launch the script
`update.sh` (or `update.bat`). This will download the most recent
InvokeAI (including bug fixes) and reinstall the environment.
You should then be able to run `invoke.sh`/`invoke.bat`.
2. If this doesn't work, you can try cleaning your system's conda
cache. This is slightly more extreme, but won't interfere with
any other python-based programs installed on your computer.
From the developer's console, run the command `conda clean -a`
and answer "yes" to all prompts.
After this is done, run `update.sh` and try again as before.
_"Corrupted configuration file."__ Everything seems to install ok, but
`invoke` complains of a corrupted configuration file and goes calls
`configure_invokeai.py` to fix, but this doesn't fix the problem.
This issue is often caused by a misconfigured configuration directive
in the `.invokeai` initialization file that contains startup settings.
This can be corrected by fixing the offending line.
First find `.invokeai`. It is a small text file located in your home
directory, `~/.invokeai` on Mac and Linux systems, and `C:\Users\*your
name*\.invokeai` on Windows systems. Open it with a text editor
(e.g. Notepad on Windows, TextEdit on Macs, or `nano` on Linux)
and look for the lines starting with `--root` and `--outdir`.
An example is here:
```cmd
--root="/home/lstein/invokeai"
--outdir="/home/lstein/invokeai/outputs"
```
There should not be whitespace before or after the directory paths,
and the paths should not end with slashes:
```cmd
--root="/home/lstein/invokeai " # wrong! no whitespace here
--root="/home\lstein\invokeai\" # wrong! shouldn't end in a slash
```
Fix the problem with your text editor and save as a **plain text**
file. This should clear the issue.
_If none of these maneuvers fixes the problem_ then please report the
problem to the [InvokeAI
Issues](https://github.com/invoke-ai/InvokeAI/issues) section, or
visit our [Discord Server](https://discord.gg/ZmtBAhwWhy) for interactive assistance.
## Updating to newer versions
This section describes how to update InvokeAI to new versions of the software.
### Updating the stable version
This distribution is changing rapidly, and we add new features on a daily basis.
To update to the latest released version (recommended), run the `update.sh`
(Linux/Mac) or `update.bat` (Windows) scripts. This will fetch the latest
release and re-run the `configure_invokeai` script to download any updated models
files that may be needed. You can also use this to add additional models that
you did not select at installation time.
You can now close the developer console and run `invoke` as before. If you get
complaints about missing models, then you may need to do the additional step of
running `configure_invokeai.py`. This happens relatively infrequently. To do this,
simply open up the developer's console again and type
`python scripts/configure_invokeai.py`.
## Troubleshooting
If you run into problems during or after installation, the InvokeAI team is
available to help you. Either create an
[Issue](https://github.com/invoke-ai/InvokeAI/issues) at our GitHub site, or
make a request for help on the "bugs-and-support" channel of our
[Discord server](https://discord.gg/ZmtBAhwWhy). We are a 100% volunteer
organization, but typically somebody will be available to help you within 24
hours, and often much sooner.

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---
title: Manual Installation, Windows
---
# :fontawesome-brands-windows: Windows
## **Notebook install (semi-automated)**
We have a
[Jupyter notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
with cell-by-cell installation steps. It will download the code in this repo as
one of the steps, so instead of cloning this repo, simply download the notebook
from the link above and load it up in VSCode (with the appropriate extensions
installed)/Jupyter/JupyterLab and start running the cells one-by-one.
Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehand.
## **Manual Install with Conda**
1. Install Anaconda3 (miniconda3 version) from [here](https://docs.anaconda.com/anaconda/install/windows/)
2. Install Git from [here](https://git-scm.com/download/win)
3. Launch Anaconda from the Windows Start menu. This will bring up a command
window. Type all the remaining commands in this window.
4. Run the command:
```batch
git clone https://github.com/invoke-ai/InvokeAI.git
```
This will create stable-diffusion folder where you will follow the rest of
the steps.
5. Enter the newly-created InvokeAI folder. From this step forward make sure that you are working in the InvokeAI directory!
```batch
cd InvokeAI
```
6. Run the following commands:
!!! todo "For systems with a CUDA (Nvidia) card:"
```bash
rmdir src # (this is a precaution in case there is already a src directory)
conda env create -f environment-cuda.yml
conda activate invokeai
(invokeai)>
```
!!! todo "For systems with an AMD card (using ROCm driver):"
```bash
rmdir src # (this is a precaution in case there is already a src directory)
conda env create -f environment-AMD.yml
conda activate invokeai
(invokeai)>
```
This will install all python requirements and activate the "invokeai" environment
which sets PATH and other environment variables properly.
7. Load the big stable diffusion weights files and a couple of smaller machine-learning models:
```bash
python scripts/configure_invokeai.py
```
!!! note
This script will lead you through the process of creating an account on Hugging Face,
accepting the terms and conditions of the Stable Diffusion model license, and
obtaining an access token for downloading. It will then download and install the
weights files for you.
Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing the
same thing.
8. Start generating images!
!!! example ""
!!! warning "IMPORTANT"
Make sure that the conda environment is activated, which should create
`(invokeai)` in front of your prompt!
=== "CLI"
```bash
python scripts/invoke.py
```
=== "local Webserver"
```bash
python scripts/invoke.py --web
```
=== "Public Webserver"
```bash
python scripts/invoke.py --web --host 0.0.0.0
```
To use an alternative model you may invoke the `!switch` command in
the CLI, or pass `--model <model_name>` during `invoke.py` launch for
either the CLI or the Web UI. See [Command Line
Client](../../deprecated/CLI.md#model-selection-and-importation). The
model names are defined in `configs/models.yaml`.
9. Subsequently, to relaunch the script, first activate the Anaconda
command window (step 3),enter the InvokeAI directory (step 5, `cd
\path\to\InvokeAI`), run `conda activate invokeai` (step 6b), and then
launch the invoke script (step 9).
!!! tip "Tildebyte has written an alternative"
["Easy peasy Windows install"](https://github.com/invoke-ai/InvokeAI/wiki/Easy-peasy-Windows-install)
which uses the Windows Powershell and pew. If you are having trouble with
Anaconda on Windows, give this a try (or try it first!)
---
This distribution is changing rapidly. If you used the `git clone` method
(step 5) to download the stable-diffusion directory, then to update to the
latest and greatest version, launch the Anaconda window, enter
`stable-diffusion`, and type:
```bash
git pull
conda env update
```
This will bring your local copy into sync with the remote one.

9
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@ -126,15 +126,6 @@ nav:
- Installing Models: 'installation/050_INSTALLING_MODELS.md'
- Installing PyPatchMatch: 'installation/060_INSTALL_PATCHMATCH.md'
- Installing xFormers: 'installation/070_INSTALL_XFORMERS.md'
- Developers Documentation: 'installation/Developers_documentation/BUILDING_BINARY_INSTALLERS.md'
- Deprecated Documentation:
- Binary Installer: 'installation/deprecated_documentation/INSTALL_BINARY.md'
- Runninng InvokeAI on Google Colab: 'installation/deprecated_documentation/INSTALL_JUPYTER.md'
- Manual Installation on Linux: 'installation/deprecated_documentation/INSTALL_LINUX.md'
- Manual Installation on macOS: 'installation/deprecated_documentation/INSTALL_MAC.md'
- Manual Installation on Windows: 'installation/deprecated_documentation/INSTALL_WINDOWS.md'
- Installing Invoke with pip: 'installation/deprecated_documentation/INSTALL_PCP.md'
- Source Installer: 'installation/deprecated_documentation/INSTALL_SOURCE.md'
- Workflows & Nodes:
- Nodes Overview: 'nodes/overview.md'
- Workflow Editor Basics: 'nodes/NODES.md'