| Argument | Shortcut | Default | Description |
|--------------------|------------|---------------------|--------------|
| `--weights ` | | `None` | Path to weights file; use `--model stable-diffusion-1.4` instead |
| `--laion400m` | `-l` | `False` | Use older LAION400m weights; use `--model=laion400m` instead |
!!! tip
On Windows systems, you may run into
problems when passing the invoke script standard backslashed path
names because the Python interpreter treats "\" as an escape.
You can either double your slashes (ick): `C:\\path\\to\\my\\file`, or
use Linux/Mac style forward slashes (better): `C:/path/to/my/file`.
## The .invokeai initialization file
To start up invoke.py with your preferred settings, place your desired
startup options in a file in your home directory named `.invokeai` The
file should contain the startup options as you would type them on the
command line (`--steps=10 --grid`), one argument per line, or a
mixture of both using any of the accepted command switch formats:
!!! example ""
```bash
--web
--steps=28
--grid
-f 0.6 -C 11.0 -A k_euler_a
```
Note that the initialization file only accepts the command line arguments.
There are additional arguments that you can provide on the `invoke>` command
line (such as `-n` or `--iterations`) that cannot be entered into this file.
Also be alert for empty blank lines at the end of the file, which will cause
an arguments error at startup time.
## List of prompt arguments
After the invoke.py script initializes, it will present you with a `invoke>`
prompt. Here you can enter information to generate images from text
([txt2img](#txt2img)), to embellish an existing image or sketch
([img2img](#img2img)), or to selectively alter chosen regions of the image
([inpainting](#inpainting)).
### txt2img
!!! example ""
```bash
invoke> waterfall and rainbow -W640 -H480
```
This will create the requested image with the dimensions 640 (width)
and 480 (height).
Here are the invoke> command that apply to txt2img:
| Argument laion400m not loaded### !switchstable-diffusion-1.4 active Stable Diffusion v1.4 waifu-diffusion not loaded Waifu Diffusion v1.3
invoke> !models laion400m not loaded### !import_modelstable-diffusion-1.4 cached Stable Diffusion v1.4 waifu-diffusion active Waifu Diffusion v1.3 invoke> !switch waifu-diffusion >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.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 >> Model loaded in 18.24s >> Max VRAM used to load the model: 2.17G >> Current VRAM usage:2.17G >> Setting Sampler to k_lms invoke> !models laion400m not loaded stable-diffusion-1.4 cached Stable Diffusion v1.4 waifu-diffusion active Waifu Diffusion v1.3 invoke> !switch stable-diffusion-1.4 >> Caching model waifu-diffusion in system RAM >> Retrieving model stable-diffusion-1.4 from system RAM cache >> Setting Sampler to k_lms invoke> !models laion400m not loaded stable-diffusion-1.4 active Stable Diffusion v1.4 waifu-diffusion cached Waifu Diffusion v1.3
invoke> !import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt >> Model import in process. Please enter the values needed to configure this model: Name for this model: waifu-diffusion Description of this model: Waifu Diffusion v1.3 Configuration file for this model: configs/stable-diffusion/v1-inference.yaml Default image width: 512 Default image height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu Diffusion v1.3 height: 512 weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.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 invoke>###!edit_model
invoke> !edit_model waifu-diffusion >> Editing model waifu-diffusion from configuration file ./configs/models.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt config: configs/stable-diffusion/v1-inference.yaml width: 512 height: 512 >> New configuration: waifu-diffusion: config: configs/stable-diffusion/v1-inference.yaml description: Waifu diffusion v1.4beta weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt height: 512 width: 512 OK to import [n]? y >> Caching model stable-diffusion-1.4 in system RAM >> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt ...======= invoke> !fix 000017.4829112.gfpgan-00.png --embiggen 3 ...lots of text... Outputs: [2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25 ``` ## History processing The CLI provides a series of convenient commands for reviewing previous actions, retrieving them, modifying them, and re-running them. ### !history The invoke script keeps track of all the commands you issue during a session, allowing you to re-run them. On Mac and Linux systems, it also writes the command-line history out to disk, giving you access to the most recent 1000 commands issued. The `!history` command will return a numbered list of all the commands issued during the session (Windows), or the most recent 1000 commands (Mac|Linux). You can then repeat a command by using the command `!NNN`, where "NNN" is the history line number. For example: ```bash invoke> !history ... [14] happy woman sitting under tree wearing broad hat and flowing garment [15] beautiful woman sitting under tree wearing broad hat and flowing garment [18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 [20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 ... invoke> !20 invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 ``` ### !fetch This command retrieves the generation parameters from a previously generated image and either loads them into the command line (Linux|Mac), or prints them out in a comment for copy-and-paste (Windows). You may provide either the name of a file in the current output directory, or a full file path. Specify path to a folder with image png files, and wildcard \*.png to retrieve the dream command used to generate the images, and save them to a file commands.txt for further processing. This example loads the generation command for a single png file: ```bash invoke> !fetch 0000015.8929913.png # the script returns the next line, ready for editing and running: invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5 ``` This one fetches the generation commands from a batch of files and stores them into `selected.txt`: ```bash invoke> !fetch outputs\selected-imgs\*.png selected.txt ``` ### !replay This command replays a text file generated by !fetch or created manually ``` invoke> !replay outputs\selected-imgs\selected.txt ``` Note that these commands may behave unexpectedly if given a PNG file that was not generated by InvokeAI. ### !search