Updates INSTALL_MAC.md

docs/installation/INSTALL_MAC.md

@@ -1,89 +1,105 @@
 # **macOS Instructions**
 
-Requirements
+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
-- Python
-- Patience
-- Apple Silicon\*
+- 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)
 
-\*I haven't tested any of this on Intel Macs but I have read that one person got it to work, so Apple Silicon might not be requried.
+## Installation
 
-Things have moved really fast and so these instructions change often
-and are often out-of-date. One of the problems is that there are so
-many different ways to run this.
-
-We are trying to build a testing setup so that when we make changes it
-doesn't always break.
-
-How to (this hasn't been 100% tested yet):
-
-First get the weights checkpoint download started - it's big:
+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)
+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.
 
-While that is downloading, open Terminal and run the following commands one at a time.
+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).
+
+Do not just copy and paste the whole thing into your terminal!
 
 ```bash
-# install brew (and Xcode command line tools):
+# Install brew (and Xcode command line tools):
 /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
 
-#
-# Now there are two different routes to get the Python (miniconda) environment up and running:
+# Now there are two options to get the Python (miniconda) environment up and running:
 # 1. Alongside pyenv
-# 2. No pyenv
+# 2. Standalone
 #
 # If you don't know what we are talking about, choose 2.
 #
-# NOW EITHER DO
-# 1. Installing alongside pyenv
+# If you are familiar with python environments, you'll know there are other options
+# for setting up the environment - you are on your own if you go one of those routes.
 
+##### BEGIN TWO DIFFERENT OPTIONS #####
+
+### BEGIN OPTION 1: Installing alongside pyenv ###
 brew install pyenv-virtualenv # you might have this from before, no problem
 pyenv install anaconda3-2022.05
 pyenv virtualenv anaconda3-2022.05
 eval "$(pyenv init -)"
 pyenv activate anaconda3-2022.05
+### END OPTION 1 ###
 
-# OR,
-# 2. Installing standalone
-# install python 3, git, cmake, protobuf:
+
+### BEGIN OPTION 2: Installing standalone ###
+# Install cmake, protobuf, and rust:
 brew install cmake protobuf rust
 
-# install miniconda (M1 arm64 version):
+# BEGIN ARCHITECTURE-DEPENDENT STEP #
+# For M1: install miniconda (M1 arm64 version):
 curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o Miniconda3-latest-MacOSX-arm64.sh
 /bin/bash Miniconda3-latest-MacOSX-arm64.sh
 
+# For Intel: install miniconda (Intel x86-64 version):
+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
+# END ARCHITECTURE-DEPENDENT STEP #
 
-# EITHER WAY,
-# continue from here
+### END OPTION 2 ###
 
-# clone the repo
+##### END TWO DIFFERENT OPTIONS #####
+
+# Clone the Invoke AI repo
 git clone https://github.com/invoke-ai/InvokeAI.git
 cd InvokeAI
 
-#
-# wait until the checkpoint file has downloaded, then proceed
-#
+### WAIT FOR THE CHECKPOINT FILE TO DOWNLOAD, THEN PROCEED ###
 
-# create symlink to checkpoint
+# We will leave the big checkpoint wherever you stashed it for long-term storage,
+# and make a link to it from the repo's folder. This allows you to use it for
+# other repos, and if you need to delete Invoke AI, you won't have to download it again.
+
+# Make the directory in the repo for the symlink
 mkdir -p models/ldm/stable-diffusion-v1/
 
-PATH_TO_CKPT="$HOME/Downloads"  # or wherever you saved sd-v1-4.ckpt
+# This is the folder where you put the checkpoint file `sd-v1-4.ckpt`
+PATH_TO_CKPT="$HOME/Downloads"
 
+# Create a link to the checkpoint
 ln -s "$PATH_TO_CKPT/sd-v1-4.ckpt" models/ldm/stable-diffusion-v1/model.ckpt
 
-# install packages
+# BEGIN ARCHITECTURE-DEPENDENT STEP #
+# For M1: Create the environment & install packages
 PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac.yaml
+
+# For Intel: Create the environment & install packages
+PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-64 conda env create -f environment-mac.yaml
+# END ARCHITECTURE-DEPENDENT STEP #
+
+# Activate the environment (you need to do this every time you want to run SD)
 conda activate ldm
 
-# only need to do this once
+# This will download some bits and pieces and make take a while
 python scripts/preload_models.py
 
-# run SD!
-python scripts/dream.py --full_precision  # half-precision requires autocast and won't work
+# Run SD!
+python scripts/dream.py
 ```
 
 The original scripts should work as well.