- stable-diffusion-2.1-base base model from
stabilityai/stable-diffusion-2-1-base
- stable-diffusion-2.1-768 768 pixel model from
stabilityai/stable-diffusion-2-1-768
- sd-inpainting-2.0 512 pixel inpainting model from
runwayml/stable-diffusion-inpainting
This PR also bumps the version number up to v2.3.1.post2
- stable-diffusion-2.1-base
base model from stabilityai/stable-diffusion-2-1-base
- stable-diffusion-2.1-768
768 pixel model from stabilityai/stable-diffusion-2-1-768
- sd-inpainting-2.0
512 pixel inpainting model from runwayml/stable-diffusion-inpainting
- Updated Spanish translation
- Updated Portuguese (Brazil) translation
- Fix a number of translation issues and add missing strings
- Fix vertical symmetry and symmetry steps issue when generation steps
is adjusted
I had inadvertently un-safe-d our translation types when migrating to Weblate.
This PR fixes that, and a number of translation string bugs that went unnoticed due to the lack of type safety,
- Add curated set of starter models based on team discussion. The final
list of starter models can be found in
`invokeai/configs/INITIAL_MODELS.yaml`
- To test model installation, I selected and installed all the models on
the list. This led to my discovering that when there are no more starter
models to display, the console front end crashes. So I made a fix to
this in which the entire starter model selection is no longer shown.
- Update model table in 050_INSTALL_MODELS.md
- Add guide to dealing with low-memory situations
- Version is now `v2.3.1`
- add new script `scripts/make_models_markdown_table.py` that parses
INITIAL_MODELS.yaml and creates markdown table for the model installation
documentation file
- update 050_INSTALLING_MODELS.md with above table, and add a warning
about additional license terms that apply to some of the models.
- Final list can be found in invokeai/configs/INITIAL_MODELS.yaml
- After installing all the models, I discovered a bug in the file
selection form that caused a crash when no remaining uninstalled
models remained. So had to fix this.
The sample_to_image method in `ldm.invoke.generator.base` was still
using ckpt-era code. As a result when the WebUI was set to show
"accurate" intermediate images, there'd be a crash. This PR corrects the
problem.
- Closes#2784
- Closes#2775
- Discord member @marcus.llewellyn reported that some civitai
2.1-derived checkpoints were not converting properly (probably
dreambooth-generated):
https://discord.com/channels/1020123559063990373/1078386197589655582/1078387806122025070
- @blessedcoolant tracked this down to a missing key that was used to
derive vector length of the CLIP model used by fetching the second
dimension of the tensor at "cond_stage_model.model.text_projection".
- On inspection, I found that the same second dimension can be recovered
from key 'cond_stage_model.model.ln_final.bias', and use that instead. I
hope this is correct; tested on multiple v1, v2 and inpainting models
and they converted correctly.
- While debugging this, I found and fixed several other issues:
- model download script was not pre-downloading the OpenCLIP
text_encoder or text_tokenizer. This is fixed.
- got rid of legacy code in `ckpt_to_diffuser.py` and replaced with
calls into `model_manager`
- more consistent status reporting in the CLI.
without this change, the project can be installed on 3.9 but not used
this also fixes the container images
Maybe we should re-enable Python 3.9 checks which would have prevented
this.
- Discord member @marcus.llewellyn reported that some civitai 2.1-derived checkpoints were
not converting properly (probably dreambooth-generated):
https://discord.com/channels/1020123559063990373/1078386197589655582/1078387806122025070
- @blessedcoolant tracked this down to a missing key that was used to
derive vector length of the CLIP model used by fetching the second
dimension of the tensor at "cond_stage_model.model.text_projection".
His proposed solution was to hardcode a value of 1024.
- On inspection, I found that the same second dimension can be
recovered from key 'cond_stage_model.model.ln_final.bias', and use
that instead. I hope this is correct; tested on multiple v1, v2 and
inpainting models and they converted correctly.
- While debugging this, I found and fixed several other issues:
- model download script was not pre-downloading the OpenCLIP
text_encoder or text_tokenizer. This is fixed.
- got rid of legacy code in `ckpt_to_diffuser.py` and replaced
with calls into `model_manager`
- more consistent status reporting in the CLI.
Root directory finding algorithm is:
2) use --root argument
2) use INVOKEAI_ROOT environment variable
3) use VIRTUAL_ENV environment variable
4) use ~/invokeai
Since developers are liable to put virtual environments in their
favorite places, not necessarily in the invokeai root directory, this PR
adds a sanity check that looks for the existence of
`VIRTUAL_ENV/invokeai.init`, and moves on to (4) if not found.
# This will constitute v2.3.1+rc2
## Windows installer enhancements
1. resize installer window to give more room for configure and download
forms
2. replace '\' with '/' in directory names to allow user to
drag-and-drop
folders into the dialogue boxes that accept directories.
3. similar change in CLI for the !import_model and !convert_model
commands
4. better error reporting when a model download fails due to network
errors
5. put the launcher scripts into a loop so that menu reappears after
invokeai, merge script, etc exits. User can quit with "Q".
6. do not try to download fp16 of sd-ft-mse-vae, since it doesn't exist.
7. cleaned up status reporting when installing models
8. Detect when install failed for some reason and print helpful error
message rather than stack trace.
9. Detect window size and resize to minimum acceptable values to provide
better display of configure and install forms.
10. Fix a bug in the CLI which prevented diffusers imported by their
repo_ids
from being correctly registered in the current session (though they
install
correctly)
11. Capitalize the "i" in Imported in the autogenerated descriptions.
Root directory finding algorithm is:
2) use --root argument
2) use INVOKEAI_ROOT environment variable
3) use VIRTUAL_ENV environment variable
4) use ~/invokeai
Since developer's are liable to put virtual environments in their
favorite places, not necessarily in the invokeai root directory, this
PR adds a sanity check that looks for the existence of
VIRTUAL_ENV/invokeai.init, and moves to (4) if not found.
