This is a step-by-step guide for using the Google Colab notebook in the Quick Start Guide to run AUTOMATIC1111. This is one of the easiest ways to use AUTOMATIC1111 because you don’t need to deal with the installation.
See install instructions on Windows PC and Mac if you prefer to run locally.
Updates
- Sept 8, 2023: Now you can use v1.6.0 version of Stable Diffusion WebUI! See specifying a version.
- July 21, 2023: This Colab notebook now supports SDXL 1.0 model!
- April 21, 2023: Google has blocked usage of Stable Diffusion with a free account. You need a paid plan to use this notebook.
Contents
- What is AUTOMATIC1111?
- What is Google Colab?
- Step-by-step instructions to run the Colab notebook
- ngrok (Optional)
- When you are done
- Runtime type supported
- Computing resources and compute units
- Models available
- Other models
- Save in Google Drive – Small models, images and settings
- Save in Google Drive – Everything
- Installing a model from URL
- Installing extensions from URL
- Extra arguments to webui
- Instruct-Pix2Pix
- Version
- Extensions
- Frequently asked questions
- Next Step
What is AUTOMATIC1111?
You should know what AUTOMATIC1111 Stable Diffusion WebUI is if you want to be a serious user of Stable Diffusion. You can choose not to use it. But you need to know what it can do because it is the gold standard in features, though not necessarily stability…
Stable Diffusion is a machine-learning model. By itself is not very user-friendly. You will need to write codes to use it. It’s a hassle. Most users use a GUI (Graphical User Interface) to use Stable Diffusion. Instead of writing codes, we write prompts in a text box and click buttons to generate images.
AUTOMATIC1111 was one of the first GUIs developed for Stable Diffusion. Although it associates with AUTOMATIC1111’s GitHub account, it has been a community effort to develop this software.
AUTOMATIC1111 is feature-rich: You can use text-to-image, image-to-image, upscaling, depth-to-image, and run and train custom models all within this GUI. Many of the tutorials on this site are demonstrated with this GUI.
What is Google Colab?
Google Colab (Google Colaboratory) is an interactive computing service offered by Google. It is a Jupyter Notebook environment that allows you to execute code. Google Colab is commonly used in data science, such as exploring deep learning models. It is a perfect setup for running Stable Diffusion WebUI.
They have three paid plans – Pay As You Go, Colab Pro, and Colab Pro+. I recommend using the Colab Pro plan. It gives you 100 compute units per month which are about 50 hours on a standard GPU. (It’s a steal) You can also get high-RAM machines, which are useful for using v2 models and some extensions.
With a paid plan, you have the option to use Premium GPU. It is an A100 processor. That comes in handy when you need to train Dreambooth models fast.
When you use Colab for AUTOMATIC1111, be sure to disconnect and shut down the notebook when you are done. It will consume compute units when the notebook is kept open.
Step-by-step instructions to run the Colab notebook
Step 1. Open the Colab notebook in Quick Start Guide. You should see the notebook with the second cell like below.
Step 2. Review username and password. You will need the credential after you start AUTOMATIC11111.
Step 3. Review Save_In_Google_Drive option. Three options are available.
- Everything: Save the whole AUTOMATIC1111 Stable Diffusion webui in your Google Drive. This option requires more maintenance. Recommended for advanced users only.
- Small models, images and settings: Saves Lora models, Embeddings, GUI Settings and all image in your Google Drive.
It will load the followings from your Google Drive.
- Models (from
output_path/models folder) - Upscalers (from
output_path/ESRGAN folder) - Lora models (from
output_path/Lora folder) - Embeddings (from
output_path/embeddings folder)
3. Nothing: Will not use your Google Drive. All data and images will be deleted after you disconnect.
You must grant permission to access Google Drive if you choose the first or the second options.
Step 4. Check the models you want to load. Currently we offer v1.4, v1.5, v1.5 inpainting, F222, anything v3, inkpunk diffusion, Mo Di diffusion, v2.1-512, v2.1-768 and v2 depth model.
If you are a first-time user, you can select the v1.5 model.
If you chose to save everything in Google Drive, the models will be downloaded to your Google Drive.
Step 6. Click the Play button on the left of the cell to start. It may warn you about needing high RAM if you don’t have a Pro subscription. Ignoring the warning is okay if you don’t use the v2.1 768 px model.
Step 7. Start-up should complete within a few minutes. How long it takes depends on how many models you include. When it is done, you should see the message below.
Step 8. Follow the gradio.live link to start AUTOMATIC1111.
Step 9. Enter the username and password you specified in the notebook.
Step 10. You should see the AUTOMATIC1111 GUI after you log in.
Put in “a cat” in the prompt text box and press Generate to test using Stable Diffusion. You should see it generates an image of a cat.
ngrok (Optional)
If you run into display issues with the GUI, you can try using ngrok instead of Gradio to establish the public connection. It is a more stable alternative to the default gradio connection.
You will need to set up a free account and get an authoken.
- Go to https://ngrok.com/
- Create an account
- Verify email
- Copy the authoken from https://dashboard.ngrok.com/get-started/your-authtoken and paste in the ngrok field in the notebook.
The Stable Diffusion cell in the notebook should look like below after you put in your ngrok authtoken.
Click the play button on the left to start running. When it is done loading, you will see a link to ngrok.io in the output under the cell. Click the ngrok.io link to start AUTOMATIC1111. The first link in the example output below is the ngrok.io link.
When you visit the ngrok link, it should show a message like below
Click on Visit Site to Start AUOTMATIC1111 GUI. Occasionally, you will see a warning message that the site is unsafe to visit. It is likely because someone used the same ngrok link to put up something malicious. Since you are the one who created this link, you can ignore the safety warning and proceed.
When you are done
When you finish using the notebook, don’t forget to click “Disconnect and delete runtime” in the top right drop-down menu. Otherwise, you will continue to consume compute credits.
Runtime type supported
You can change the runtime type by clicking Runtime -> Change Runtime type in the top menu.
GPUs and TPUs
This notebook supports the following runtime types.
- T4 GPU (recommended)
- A100 GPU
- V100 GPU
Don’t use CPU or TPU. TPU is not compatible with Stable Diffusion WebUI.
RAM
High RAM should be used.
Computing resources and compute units
To view computing resources and credits, click the downward caret next to the runtime type (E.g. T4, High RAM) on the top right. You will see the remaining compute units and usage rate.
Models available
For your convenience, the notebook has options to load some popular models. You will find a brief description of them in this section.
v1 models
v1.4 model
v1.4 model is the first publicly released Stable Diffusion base model.
v1.5 model
v1.5 model is released after 1.4. It is the last v1 model. Images from this model is very similar to v1.4. You can treat the v1.5 model as the default v1 base model.
v1.5 inpainting model
A special model trained for inpainting.
F222
F222 is good at generating photo-realistic images. It is good at generating females with correct anatomy.
Caution: F222 is prone to generating explicit images. Suppress explicit images with a prompt “dress” or a negative prompt “nude”.
Dreamshaper
Dreamshaper is easy to use and good at generating a popular photorealistic illustration style. It is an easy way to “cheat” and get good images without a good prompt!
Open Journey Model
Open Journey is a model fine-tuned with images generated by Mid Journey v4. It has a different aesthetic and is a good general-purpose model.
Triggering keyword: mdjrny-v4 style
Anything v3
Anything V3 is a special-purpose model trained to produce high-quality anime-style images. You can use danbooru tags (like 1girl, white hair) in the text prompt.
It’s useful for casting celebrities to amine style, which can then be blended seamlessly with illustrative elements.
Inkpunk Diffusion
Inkpunk Diffusion is a Dreambooth-trained model with a very distinct illustration style.
Use keyword: nvinkpunk
v2 models
v2 models are the newest base models released by Stability AI. It is generally harder to use and is not recommended for beginners.
v2.1 768 model
The v2.1-768 model is the latest high-resolution v2 model. The native resolution is 768×768 pixels. Make sure to set at least one side of the image to 768 pixels. It is imperative to use negative prompts in v2 models.
You will need Colab Pro to use this model because it needs a high RAM instance.
v2.1 512 model
The v2.1-512 model is the lower-resolution version of the v2.1 model.
v2 depth model
v2 depth model extracts depth information from an input image and uses it to guide image generation. See the tutorial on depth-to-image.
SDXL model
This Coalb notebook supports SDXL 1.0 base and refiner models.
Select SDXL_1 to load the SDXL 1.0 model.
Important: Don’t use VAE from v1 models. Go to Settings > Stable Diffusion. Set SD VAE to AUTOMATIC or None.
Check out some SDXL prompts to get started.
Other models
Here are some models that you may be interested in.
See more realistic models here.
Dreamlike Photoreal
Dreamlike Photoreal Model Page
Model download URL
https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0/resolve/main/dreamlike-photoreal-2.0.safetensorsDreamlike Photoreal model is good at generating beautiful females with correct anatomy. It is similar to F222.
triggering keyword: photo
Caution: This model is prone to generating explicit photos. Suppress explicit images with a prompt “dress” or a negative prompt “nude”.
Lyriel
Lyriel excels in artistic style and is good at rendering a variety of subjects, ranging from portraits to objects.
Model download URL:
https://civitai.com/api/download/models/50127Deliberate v2
Deliberate v2 is a well-trained model capable of generating photorealistic illustrations, anime, and more.
Model download URL
https://civitai.com/api/download/models/15236Save in Google Drive – Small models, images and settings
I recommend this to most users. This is designed to save small data files to Google Drive but download big files. So your Google Drive won’t be used up by Stable Diffusion.
You select Small models, images and settings option. The following are saved in your Google Drive.
- All generated images
- GUI settings
- Prompt and parameters used in the last generated image
- Embeddings (Path: AI_PICS/embeddings)
- Lora models (Path: AI_PICS/Lora)
- Upscalers (Path: AI_PICS/ESRGAN)
- Hypernetworks (Path: AI_PICS/hypernetworks)
Next time you run the notebook, all of the above will be available.
This option will not save any models in your Google Drive. But it will load all the models you put in AI_PICS/models.
You only need to put models you frequent but NOT in the Notebook’s model list in AI_PICS/models. Since model files are large (2 to 7 GB), you don’t want to put too many in your Google Drive. (Free storage of Google Drive is only 15 GB)
Installing embeddings
Embeddings are lightweight files used to modify styles or inject objects. To install embeddings, drag and drop the file to stable-diffusion-webui > embeddings.
Embeddings are reloaded whenever you switch models. You will get a confirmation in the log message on Colab.
Installing LoRA
LoRA (Low-Rank Adaptation) models are small patches that can be applied to the model checkpoints. Their sizes are small, usually between 3-200 MB, making them easy to store. They are good alternatives to models.
To install a LoRA model, drag and drop the model to the directory stable-diffusion-webui > models > Lora in the file explorer panel.
The LoRA model will be saved to your Google Drive under AI_PICS > Lora if Use_Google_Drive is selected. You can reuse the model next time if you select the same option.
Alternatively, you can put a Lora model in your Google Drive in AI_PICS > Lora if you use the google drive option. It uploads faster this way.
Installing Upscalers
You can use upscalers in your Google Drive. Just put them in AI_PICS > ESRGAN folder in your Google Drive. Next time when you start the notebook with the Use_Google_Drive option.
Using models in Google Drive
You can use models in your Google Drive. You must put the models in the following default location.
AI_PICS/modelsAll models within this folder will be loaded during start-up.
Installing hypernetworks
To install hypernetworks, put them in the following location
AI_PICS/hypernetworksSave in Google Drive – Everything
This option saves the whole Stable Diffusion Webui folder in your Google Drive. The default location is AI_PIC > stable-diffusion-webui. Installing models is no different from Windows or Mac. Below are the folder paths
- Models: AI_PICS/stable-diffusion-webui/models/Stable-diffusion
- Upscalers: AI_PICS/stable-diffusion-webui/models/ESRGAN
- Lora: AI_PICS/stable-diffusion-webui/models/Lora
- Embeddings: AI_PICS/stable-diffusion-webui/embeddings
- Hypernetworks: AI_PICS/stable-diffusion-webui/hypernetworks
Installing a model from URL
You can install models from URLs using the Model_from_URL field. Currently, you can only install v1 models.
Installing a model from HuggingFace
Below’s an example input for installing DreamShaper from HuggingFace
https://huggingface.co/Lykon/DreamShaper/resolve/main/Dreamshaper_3.32_baked_vae_clip_fix_half.ckpt(Link may not be correct as this model is updated frequently)
Installing a model from Civitai
You will need to copy the URL link for downloading the model. Don’t use the URL of the model page.
To copy the download link, right-click the Download button and select Copy Link Address.
Saving a copy in Google Drive
You can optionally save a copy of the models in your Google Drive using Save_a_copy_in_Google_Drive. They will be saved in the model loading location. AI_PICS/models.
The next time you start the notebook, the models you saved in Google Drive will be automatically loaded.
Use this option only when you use the recommended setting: Save small models and images in Google Drive.
Installing extensions from URL
You can install any number of extensions by using this field. You will need the URL of the Github page of the extension.
For example, put in the following if you want to install the Civitai model extension.
https://github.com/civitai/sd_civitai_extensionYou can also install multiple extensions. The URLs need to be separated with commas. For example, the following URLs install the Civitai and the multi-diffusion extensions.
https://github.com/civitai/sd_civitai_extension,https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111Extra arguments to webui
You can add extra arguments to the Web-UI by using the Extra_arguments field.
For example, if you use the lycoris extension, it is handy to use the extra webui argument --lyco-dir to specify a custom lycoris model directory in your Google Drive.
Other useful arguments are
--api. Allow API access. Useful for some applications, e.g. the PhotoShop Automatic1111 plugin.
Instruct-Pix2Pix
Instruct-Pix2Pix is a Stable Diffusion model that lets you edit photos with text instruction alone.
To use the instruct-Pix2Pix model, check the instruct_pix2pix_model checkbox. Follow the instructions in this tutorial.
Version
Now you can specify the version of Stable Diffusion WebUI you want to load. Use this at your own risk, as I only test the version saved.
Notes on some versions
v1.6.0: You need to add--disable-model-loading-ram-optimizationin the Extra_arguments field.
Extensions
ControlNet
ControlNet is a Stable Diffusion extension that can copy the composition and pose of the input image and more. ControlNet is taken the Stable Diffusion community by storm because there is so much you can do with it. Here are some examples
This notebook supports ControlNet. See the tutorial article.
Deforum – Making Videos using Stable Diffusion
You can make videos with text prompts using the Deforum extension. See this tutorial for a walkthrough.
Regional Prompter
Regional prompter lets you use different prompts for different regions of the image. It is a valuable extension for controlling the composition and placement of objects.
After Detailer
After Detailer (!adetailer) extension fixes faces and hands automatically when you generate images.
Openpose editor
Openpose editor is an extension that lets you edit the openpose control image. It is useful for manipulating the pose of an image generation with ControlNet. It is used with ControlNet.
AnimateDiff
AnimateDiff lets you create short videos from a text prompt. You can any Stable Diffusion model and LoRA. Follow this tutorial to learn how to use it.
text2video
Text2video lets you create short videos from a text prompt using a model called Modelscope. Follow this tutorial to learn how to use it.
Frequently asked questions
Do I need a paid account to use the notebook?
Yes, you need a paid account to use this notebook. Google has blocked the free usage of Stable Diffusion.
Do I need to use ngrok?
You don’t need to use ngrok to use the Colab notebook. In my experience, ngrok provides a more stable connection between your browser and the GUI. If you experience issues like buttons not responding, you should try ngrok.
Why do I keep getting disconnected?
Two possible reasons:
- There’s a human verification shortly after starting each Colab notebook session. You will get disconnected if you do not respond to it. Make sure to switch back to the Colab notebook and check for verification.
- You are using a free account. Google has blocked A1111 in Colab. Get Colab Pro.
Is saving everything in Google Drive faster?
The first time is slower because you need to download things to your Google Drive, which has a slower speed. Later times range from 20% faster to 50% slower. This has something to do with the speed of accessing data in Google Drive.
Can I use the dreambooth models I trained?
Yes. Models typically need to be converted to be used in AUTOMATIC1111. But if you use the notebook in my Dreambooth tutorial, it has already been converted for you.
You will need to select save “small models, images and settings” in Google Drive option. Put your dreambooth model in AI_PICS/models. You can rename the model file if desired.
How to enable API?
You can use AUMATIC1111 as an API server. Add the following to Extra Web-UI arguments.
--apiThe server’s URL is the same as the one you access the Web-UI. (i.e. the gradio or ngrok link)
Why do my SDXL images look garbled?
Check to make sure you are not using a VAE from v1 models. Check Settings > Stable Diffusion > SD VAE. Set it to None or Automatic.
Next Step
If you are new to Stable Diffusion, check out the Absolute beginner’s guide.
I have an issue with ngrok, link don’t work when started, if i leave ngrok and use only gradio all works fine
That has more to do with ngrok’s service. I can test it out next time I upgrade the notebook.
Hi Andrew .)
First of all, thank you for your incredible work on Colab!
Since the last update 23-09-23 the system memory on Colab seems to pile up until crash.
Is it me or maybe the last update changed something related?
Hi, can you tell me how to reproduce the crash?
Hi Andrew,
thank you for the reply.
We were using sdxl with regional prompt on a standard colab profile, T4, 12gb system ram.
Performing rendering the amount of the system ram rise, as expected, than remain up, say roughly 11,5 Gb.
The next rendering the system ram continues to rise until max , piling up, than the system disconnects.
The day before, the 22th, we used this way Colab with the same sdxl configurations and prompts, working fine all the day.
Thanks
Just updated the notebook. Can you try with the new one?
Hi Andrew,
it’s working .)
Runs smoothly, multiple renderings in sequence, system ram lower than 3gb, not piling up until now .)
Thank you so much!
.)
Hi. I’m looking to use the train function, and I want to do a custom prompt template file for the textual inversion part. In a local install of a1111 I should put these text files in the /textual_inversion_templates directory. Is there a way to create this directory for the colab to find it?
Can you try using the file explorer on text to create?
Which username and password should we use to run the installation cell? (where it says just “a”…is it a new user and password we would use for the Colab/SD notebook orthe username and password I have for GitHub? or my Google Proo account..? thanks!
This password is for protecting your A1111 from others to access. You can set to anything you like.
Hello, I tried to add models manually into the models folder, but A1111 only sees the ckpt files and not the safetensors ones, is there something to enable somewhere ?
That shouldn’t be. It must be the model link being incorrect. Use a link that would download the file when you visit it on browser.
Hi, I tried google colab with version 1.6 but when I try to use controlent with img2img I get this error “RuntimeError: mat1 and mat2 shapes cannot be multiplied (154×2048 and 768×320)” what can it be? thank you
Thank you for providing the updated version. Unfortunately, I have encountered an issue with Torch, as detailed below. Could you kindly offer guidance on how to resolve this matter? thank you
“Traceback (most recent call last):
File “/content//stable-diffusion-webui/launch.py”, line 48, in
main()
File “/content//stable-diffusion-webui/launch.py”, line 39, in main
prepare_environment()
File “/content/stable-diffusion-webui/modules/launch_utils.py”, line 356, in prepare_environment
raise RuntimeError(
RuntimeError: Torch is not able to use GPU; add –skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check”
It appears you didn’t select to use gpu. change the runtime type to use a gpu.
you have to repeat the steps each time you run the notebook. make sure also you have disconnected the GPU before stopping your work. else colab will consider the GPU “running” and will use up your credits.
this was in “reply” to msaliza. and this i am typing in reply to my comment. lets see where it is posted. do I have to do something special for a “reply” to a comment?
The reply function is glitchy. Sometimes the replied message doesn’t follow the thread but appears at the top.
Appreciate if someone in the knows can tell me how to fix it.
Thank you so much for putting this together. Up until now, I’ve never had an issue running the notebook, but now I get an error (using the same settings that I’ve always used) and I’m not sure what’s going on. Before, the only assets created in Drive were what I added or created. Now I can see that every time I hit play, it starts uploading a ton of random images and things.
/content/drive/MyDrive/AI_PICS/stable-diffusion-webui
WEBUI ARGUMENTS: –gradio-img2img-tool color-sketch –enable-insecure-extension-access –gradio-queue –xformers –share –gradio-auth a:a –disable-model-loading-ram-optimization
Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]
Version: v1.5.0
Commit hash: a3ddf464a2ed24c999f67ddfef7969f8291567be
Installing xformers
Launching Web UI with arguments: –gradio-img2img-tool color-sketch –enable-insecure-extension-access –gradio-queue –xformers –share –gradio-auth a:a –disable-model-loading-ram-optimization
2023-09-10 14:16:17.861903: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-09-10 14:16:18.867965: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
usage: launch.py
[-h]
[–update-all-extensions]
[–skip-python-version-check]
[–skip-torch-cuda-test]
[–reinstall-xformers]
[–reinstall-torch]
[–update-check]
[–test-server]
[–skip-prepare-environment]
[–skip-install]
[–do-not-download-clip]
[–data-dir DATA_DIR]
[–config CONFIG]
[–ckpt CKPT]
[–ckpt-dir CKPT_DIR]
[–vae-dir VAE_DIR]
[–gfpgan-dir GFPGAN_DIR]
[–gfpgan-model GFPGAN_MODEL]
[–no-half]
[–no-half-vae]
[–no-progressbar-hiding]
[–max-batch-count MAX_BATCH_COUNT]
[–embeddings-dir EMBEDDINGS_DIR]
[–textual-inversion-templates-dir TEXTUAL_INVERSION_TEMPLATES_DIR]
[–hypernetwork-dir HYPERNETWORK_DIR]
[–localizations-dir LOCALIZATIONS_DIR]
[–allow-code]
[–medvram]
[–lowvram]
[–lowram]
[–always-batch-cond-uncond]
[–unload-gfpgan]
[–precision {full,autocast}]
[–upcast-sampling]
[–share]
[–ngrok NGROK]
[–ngrok-region NGROK_REGION]
[–ngrok-options NGROK_OPTIONS]
[–enable-insecure-extension-access]
[–codeformer-models-path CODEFORMER_MODELS_PATH]
[–gfpgan-models-path GFPGAN_MODELS_PATH]
[–esrgan-models-path ESRGAN_MODELS_PATH]
[–bsrgan-models-path BSRGAN_MODELS_PATH]
[–realesrgan-models-path REALESRGAN_MODELS_PATH]
[–clip-models-path CLIP_MODELS_PATH]
[–xformers]
[–force-enable-xformers]
[–xformers-flash-attention]
[–deepdanbooru]
[–opt-split-attention]
[–opt-sub-quad-attention]
[–sub-quad-q-chunk-size SUB_QUAD_Q_CHUNK_SIZE]
[–sub-quad-kv-chunk-size SUB_QUAD_KV_CHUNK_SIZE]
[–sub-quad-chunk-threshold SUB_QUAD_CHUNK_THRESHOLD]
[–opt-split-attention-invokeai]
[–opt-split-attention-v1]
[–opt-sdp-attention]
[–opt-sdp-no-mem-attention]
[–disable-opt-split-attention]
[–disable-nan-check]
[–use-cpu USE_CPU [USE_CPU …]]
[–listen]
[–port PORT]
[–show-negative-prompt]
[–ui-config-file UI_CONFIG_FILE]
[–hide-ui-dir-config]
[–freeze-settings]
[–ui-settings-file UI_SETTINGS_FILE]
[–gradio-debug]
[–gradio-auth GRADIO_AUTH]
[–gradio-auth-path GRADIO_AUTH_PATH]
[–gradio-img2img-tool GRADIO_IMG2IMG_TOOL]
[–gradio-inpaint-tool GRADIO_INPAINT_TOOL]
[–gradio-allowed-path GRADIO_ALLOWED_PATH]
[–opt-channelslast]
[–styles-file STYLES_FILE]
[–autolaunch]
[–theme THEME]
[–use-textbox-seed]
[–disable-console-progressbars]
[–enable-console-prompts]
[–vae-path VAE_PATH]
[–disable-safe-unpickle]
[–api]
[–api-auth API_AUTH]
[–api-log]
[–nowebui]
[–ui-debug-mode]
[–device-id DEVICE_ID]
[–administrator]
[–cors-allow-origins CORS_ALLOW_ORIGINS]
[–cors-allow-origins-regex CORS_ALLOW_ORIGINS_REGEX]
[–tls-keyfile TLS_KEYFILE]
[–tls-certfile TLS_CERTFILE]
[–disable-tls-verify]
[–server-name SERVER_NAME]
[–gradio-queue]
[–no-gradio-queue]
[–skip-version-check]
[–no-hashing]
[–no-download-sd-model]
[–subpath SUBPATH]
[–add-stop-route]
[–api-server-stop]
[–timeout-keep-alive TIMEOUT_KEEP_ALIVE]
[–ldsr-models-path LDSR_MODELS_PATH]
[–lora-dir LORA_DIR]
[–lyco-dir-backcompat LYCO_DIR_BACKCOMPAT]
[–scunet-models-path SCUNET_MODELS_PATH]
[–swinir-models-path SWINIR_MODELS_PATH]
launch.py: error: unrecognized arguments: –disable-model-loading-ram-optimization
Hi, it appears that you save the whole thing to your google drive. You can either:
1. use the recommended save setting. This option is preferred and is faster.
2. If not, delete the whole stable-diffusion-webui directory in your google drive and restart.
Hi Andrew
I tested the new version on the colab, but I can’t select a model. Below is the error. This error repeats each time I select a checkpoint model. Is it because 1.6.0 is not ready for colab yet? Or did I miss something?
>>>
Failed to create model quickly; will retry using slow method.
changing setting sd_model_checkpoint to revAnimated_v122.safetensors: NotImplementedError
Traceback (most recent call last):
File “/content/stable-diffusion-webui/modules/options.py”, line 140, in set
option.onchange()
File “/content/stable-diffusion-webui/modules/call_queue.py”, line 13, in f
res = func(*args, **kwargs)
File “/content/stable-diffusion-webui/modules/initialize_util.py”, line 170, in
shared.opts.onchange(“sd_model_checkpoint”, wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False)
File “/content/stable-diffusion-webui/modules/sd_models.py”, line 751, in reload_model_weights
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
File “/content/stable-diffusion-webui/modules/sd_models.py”, line 611, in load_model
sd_model = instantiate_from_config(sd_config.model)
File “/content/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/util.py”, line 89, in instantiate_from_config
return get_obj_from_str(config[“target”])(**config.get(“params”, dict())).cuda()
File “/content/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py”, line 550, in __init__
super().__init__(conditioning_key=conditioning_key, *args, **kwargs)
File “/content/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py”, line 92, in __init__
self.model = DiffusionWrapper(unet_config, conditioning_key)
File “/content/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py”, line 1314, in __init__
self.diffusion_model = instantiate_from_config(diff_model_config)
File “/content/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/util.py”, line 89, in instantiate_from_config
return get_obj_from_str(config[“target”])(**config.get(“params”, dict())).cuda()
File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 905, in cuda
return self._apply(lambda t: t.cuda(device))
File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 797, in _apply
module._apply(fn)
File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 797, in _apply
module._apply(fn)
File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 820, in _apply
param_applied = fn(param)
File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 905, in
return self._apply(lambda t: t.cuda(device))
NotImplementedError: Cannot copy out of meta tensor; no data!
Hi Andrew again
I re-refreshed the colab and re-saved a copy. I tried again and now I can select the checkpoint models.
It seems all work fine. However, I have the erros as below (the first one) on the terminal cell. With the errors, I can still use 1.6.0 without any noticable issues. Can I just ignore the error messages?
And, if I type v1.5.2, I have a different error as below (the secone one) and the start link is not there. Do I have to delete the “–disable-model-loading-ram-optimization” extra argument if I want to use 1.5.2?
>>>>>>>>>>>>>>>>>
>>> the first error >>>
>>>>>>>>>>>>>>>>>
ERROR: Exception in ASGI application
Traceback (most recent call last):
File “/usr/local/lib/python3.10/dist-packages/uvicorn/protocols/websockets/websockets_impl.py”, line 247, in run_asgi
result = await self.app(self.scope, self.asgi_receive, self.asgi_send)
File “/usr/local/lib/python3.10/dist-packages/uvicorn/middleware/proxy_headers.py”, line 84, in __call__
return await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/fastapi/applications.py”, line 273, in __call__
await super().__call__(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/applications.py”, line 122, in __call__
await self.middleware_stack(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py”, line 149, in __call__
await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/middleware/cors.py”, line 76, in __call__
await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/middleware/gzip.py”, line 26, in __call__
await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/middleware/exceptions.py”, line 79, in __call__
raise exc
File “/usr/local/lib/python3.10/dist-packages/starlette/middleware/exceptions.py”, line 68, in __call__
await self.app(scope, receive, sender)
File “/usr/local/lib/python3.10/dist-packages/fastapi/middleware/asyncexitstack.py”, line 21, in __call__
raise e
File “/usr/local/lib/python3.10/dist-packages/fastapi/middleware/asyncexitstack.py”, line 18, in __call__
await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/routing.py”, line 718, in __call__
await route.handle(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/routing.py”, line 341, in handle
await self.app(scope, receive, send)
File “/usr/local/lib/python3.10/dist-packages/starlette/routing.py”, line 82, in app
await func(session)
File “/usr/local/lib/python3.10/dist-packages/fastapi/routing.py”, line 289, in app
await dependant.call(**values)
File “/usr/local/lib/python3.10/dist-packages/gradio/routes.py”, line 604, in join_queue
session_info = await asyncio.wait_for(
File “/usr/lib/python3.10/asyncio/tasks.py”, line 445, in wait_for
return fut.result()
File “/usr/local/lib/python3.10/dist-packages/starlette/websockets.py”, line 133, in receive_json
self._raise_on_disconnect(message)
File “/usr/local/lib/python3.10/dist-packages/starlette/websockets.py”, line 105, in _raise_on_disconnect
raise WebSocketDisconnect(message[“code”])
starlette.websockets.WebSocketDisconnect: 1006
>>>>>>>>>>>>>>>>>>>
>>> the second error >>>
>>>>>>>>>>>>>>>>>>>
Launching Web UI with arguments: –gradio-img2img-tool color-sketch –enable-insecure-extension-access –gradio-queue –xformers –ngrok 2PuZKHTxXKtkZwtMS5AhOhbLGHu_S219oSkBNFprycSHH9Z6 –disable-model-loading-ram-optimization
2023-09-08 11:44:17.362216: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-09-08 11:44:18.323487: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
usage: launch.py
[-h]
[–update-all-extensions]
[–skip-python-version-check]
[–skip-torch-cuda-test]
[–reinstall-xformers]
[–reinstall-torch]
[–update-check]
[–test-server]
[–skip-prepare-environment]
[–skip-install]
[–do-not-download-clip]
[–data-dir DATA_DIR]
[–config CONFIG]
[–ckpt CKPT]
[–ckpt-dir CKPT_DIR]
[–vae-dir VAE_DIR]
[–gfpgan-dir GFPGAN_DIR]
[–gfpgan-model GFPGAN_MODEL]
[–no-half]
[–no-half-vae]
[–no-progressbar-hiding]
[–max-batch-count MAX_BATCH_COUNT]
[–embeddings-dir EMBEDDINGS_DIR]
[–textual-inversion-templates-dir TEXTUAL_INVERSION_TEMPLATES_DIR]
[–hypernetwork-dir HYPERNETWORK_DIR]
[–localizations-dir LOCALIZATIONS_DIR]
[–allow-code]
[–medvram]
[–lowvram]
[–lowram]
[–always-batch-cond-uncond]
[–unload-gfpgan]
[–precision {full,autocast}]
[–upcast-sampling]
[–share]
[–ngrok NGROK]
[–ngrok-region NGROK_REGION]
[–ngrok-options NGROK_OPTIONS]
[–enable-insecure-extension-access]
[–codeformer-models-path CODEFORMER_MODELS_PATH]
[–gfpgan-models-path GFPGAN_MODELS_PATH]
[–esrgan-models-path ESRGAN_MODELS_PATH]
[–bsrgan-models-path BSRGAN_MODELS_PATH]
[–realesrgan-models-path REALESRGAN_MODELS_PATH]
[–clip-models-path CLIP_MODELS_PATH]
[–xformers]
[–force-enable-xformers]
[–xformers-flash-attention]
[–deepdanbooru]
[–opt-split-attention]
[–opt-sub-quad-attention]
[–sub-quad-q-chunk-size SUB_QUAD_Q_CHUNK_SIZE]
[–sub-quad-kv-chunk-size SUB_QUAD_KV_CHUNK_SIZE]
[–sub-quad-chunk-threshold SUB_QUAD_CHUNK_THRESHOLD]
[–opt-split-attention-invokeai]
[–opt-split-attention-v1]
[–opt-sdp-attention]
[–opt-sdp-no-mem-attention]
[–disable-opt-split-attention]
[–disable-nan-check]
[–use-cpu USE_CPU [USE_CPU …]]
[–listen]
[–port PORT]
[–show-negative-prompt]
[–ui-config-file UI_CONFIG_FILE]
[–hide-ui-dir-config]
[–freeze-settings]
[–ui-settings-file UI_SETTINGS_FILE]
[–gradio-debug]
[–gradio-auth GRADIO_AUTH]
[–gradio-auth-path GRADIO_AUTH_PATH]
[–gradio-img2img-tool GRADIO_IMG2IMG_TOOL]
[–gradio-inpaint-tool GRADIO_INPAINT_TOOL]
[–gradio-allowed-path GRADIO_ALLOWED_PATH]
[–opt-channelslast]
[–styles-file STYLES_FILE]
[–autolaunch]
[–theme THEME]
[–use-textbox-seed]
[–disable-console-progressbars]
[–enable-console-prompts]
[–vae-path VAE_PATH]
[–disable-safe-unpickle]
[–api]
[–api-auth API_AUTH]
[–api-log]
[–nowebui]
[–ui-debug-mode]
[–device-id DEVICE_ID]
[–administrator]
[–cors-allow-origins CORS_ALLOW_ORIGINS]
[–cors-allow-origins-regex CORS_ALLOW_ORIGINS_REGEX]
[–tls-keyfile TLS_KEYFILE]
[–tls-certfile TLS_CERTFILE]
[–disable-tls-verify]
[–server-name SERVER_NAME]
[–gradio-queue]
[–no-gradio-queue]
[–skip-version-check]
[–no-hashing]
[–no-download-sd-model]
[–subpath SUBPATH]
[–add-stop-route]
[–api-server-stop]
[–timeout-keep-alive TIMEOUT_KEEP_ALIVE]
[–deforum-api]
[–deforum-simple-api]
[–deforum-run-now DEFORUM_RUN_NOW]
[–deforum-terminate-after-run-now]
[–controlnet-dir CONTROLNET_DIR]
[–controlnet-annotator-models-path CONTROLNET_ANNOTATOR_MODELS_PATH]
[–no-half-controlnet]
[–controlnet-preprocessor-cache-size CONTROLNET_PREPROCESSOR_CACHE_SIZE]
[–controlnet-loglevel {DEBUG,INFO,WARNING,ERROR,CRITICAL}]
[–ldsr-models-path LDSR_MODELS_PATH]
[–lora-dir LORA_DIR]
[–lyco-dir-backcompat LYCO_DIR_BACKCOMPAT]
[–scunet-models-path SCUNET_MODELS_PATH]
[–swinir-models-path SWINIR_MODELS_PATH]
launch.py: error: unrecognized arguments: –disable-model-loading-ram-optimization
I don’t see the error message on v1.6.0.
Yes, the disable model loading option is only for v1.6.0
Thank you for your reply, Andrew.
Hope the compatibility issue is fixed soon. Appreciate your work always.
A fix is released. Refresh the notebook to get v1.6.0
Hi Andrew
First of all, thank you for your work for the colab.
Do you have a plan to update to 1.6.0?
Yes but v1.6.0 is not compatible with colab yet. waiting for a fix.
Hi Andrew,
thank you sooo much!
Hello, I’ve been using your colab, and seen that you have changed defautl sampler and added new 3M samplers to it. I have updated yesterday but do not see them in the list, and the default one is still euler. Any ideas how to fix this?
Are they one of those that are added in v1.6? It is not compatible with colab yet.
Thank you for a great tutorial. I have been successfully connected for the first time. However, I cannot connect to the same WebUI when I shut down my computer. Does this mean that I should go through all the steps again and again in order to access stable diffusion WebUI?
Hi Andrew,
Big thanks for the grat work!
Howerver, could you tell me how to keep the promt styles i saved? everytime i resart the notebook they just disapear.
Thank you !
I have added saving styles to google drive. enjoy!
You can try to use the memory fix, run this before your code:
# MEMFIX
!curl -Lo memfix.zip https://github.com/nolanaatama/microsoftexcel/raw/main/memfix.zip
!unzip /content/memfix.zip
!apt -y update -qq
%env LD_PRELOAD=/content/libtcmalloc_minimal.so.4
Hey!
Just wanted to say that in the latest version of notebook doesn’t work upscales for Deforum. This is because libvulkan1 is missing by default. You need to add !apt-get install libvulkan1 to the installDeforum function.
Oh! And Deforum need ControlNet. You can install it by default with Deforum )
Thanks for reporting! I added controlnet to deforum. The libvulkan1 library doesn’t seem to be necessary though.
Did you try setup checkbox Deforum -> Output -> Upscale without libvulkan1 library and check the result? In my case it doesn’t work.
You are right. Thanks for the command! Added.