Instructions:
1. Download LoRA .safetensors files of your choice and place in
`INVOKEAIROOT/loras`. Unlike the draft version of this, the file
names can contain underscores and alphanumerics. Names with
arbitrary unicode characters are not supported.
2. Add `withLora(lora-file-basename,weight)` to your prompt. The
weight is optional and will default to 1.0. A few examples, assuming
that a LoRA file named `loras/sushi.safetensors` is present:
```
family sitting at dinner table eating sushi withLora(sushi,0.9)
family sitting at dinner table eating sushi withLora(sushi, 0.75)
family sitting at dinner table eating sushi withLora(sushi)
```
Multiple `withLora()` prompt fragments are allowed. The weight can be
arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher
weights make the LoRA's influence stronger.
In my limited testing, I found it useful to reduce the CFG to avoid
oversharpening. Also I got better results when running the LoRA on top
of the model on which it was based during training.
Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice
versa. You will get a nasty stack trace. This needs to be cleaned up.
3. You can change the location of the `loras` directory by passing the
`--lora_directory` option to `invokeai.
Documentation can be found in docs/features/LORAS.md.
- Allow invokeai-update to update using a release, tag or branch.
- Allow CLI's root directory update routine to update directory
contents regardless of whether current version is released.
- In model importation routine, clarify wording of instructions when user is
asked to choose the type of model being imported.
This commit fixes bugs related to the on-the-fly conversion and loading of
legacy checkpoint models built on SD-2.0 base.
- When legacy checkpoints built on SD-2.0 models were converted
on-the-fly using --ckpt_convert, generation would crash with a
precision incompatibility error.
- In addition, broken logic was causing some 2.0-derived ckpt files to
be converted into diffusers and then processed through the legacy
generation routines - not good.
- installer now installs the pretty dialog-based console launcher
- added dialogrc for custom colors
- add updater to download new launcher when users do an update
This commit enhances support for V2 variant (epsilon and v-predict)
import and conversion to diffusers, by prompting the user to select
the proper config file during startup time autoimport as well as
in the invokeai installer script..
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts
the global diffusers model cache to work with the 0.14 diffusers
layout of placing models in HF_HOME/hub rather than HF_HOME/diffusers.
- Crash would occur at the end of this sequence:
- launch CLI
- !convert <URL pointing to a legacy ckpt file>
- Answer "Y" when asked to delete original .ckpt file
- This commit modifies model_manager.heuristic_import()
to silently delete the downloaded legacy file after
it has been converted into a diffusers model. The user
is no longer asked to approve deletion.
NB: This should be cherry-picked into main once refactor
is done.
- 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.
- 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)
- Capitalize the "i" in Imported in the autogenerated descriptions.
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
Enhancements:
1. Directory-based imports will not attempt to import components of diffusers models.
2. Diffuser directory imports now supported
3. Files that end with .ckpt that are not Stable Diffusion models (such as VAEs) are
skipped during import.
Bugs identified in Psychedelicious's review:
1. The invokeai-configure form now tracks the current contents of `invokeai.init` correctly.
2. The autoencoders are no longer treated like installable models, but instead are
mandatory support models. They will no longer appear in `models.yaml`
Bugs identified in Damian's review:
1. If invokeai-model-install is started before the root directory is initialized, it will
call invokeai-configure to fix the matter.
2. Fix bug that was causing empty `models.yaml` under certain conditions.
3. Made import textbox smaller
4. Hide the "convert to diffusers" options if nothing to import.
- Fixed the test for token length; tested on several .pt and .bin files
- Also added a __main__ entrypoint for CLI.py, to make pdb debugging a bit
more convenient.
- The checkpoint conversion script was generating diffusers models
with the safety checker set to null. This resulted in models
that could not be merged with ones that have the safety checker
activated.
- This PR fixes the issue by incorporating the safety checker into
all 1.x-derived checkpoints, regardless of user's nsfw_checker setting.
- quashed multiple bugs in model conversion and importing
- found old issue in handling of resume of interrupted downloads
- will require extensive testing
