Added Model rescale and prepared a release upgrade

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Jaret Burkett committed 2023-08-01 13:49:54 -06:00
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@@ -40,6 +40,8 @@ pip3 install -r requirements.txt
I have so many hodge podge scripts I am going to be moving over to this that I use in my ML work. But this is what is
here so far.
---
### LoRA (lierla), LoCON (LyCORIS) extractor
It is based on the extractor in the [LyCORIS](https://github.com/KohakuBlueleaf/LyCORIS) tool, but adding some QOL features
@@ -64,6 +66,31 @@ Most people used fixed, which is traditional fixed dimension extraction.
`process` is an array of different processes to run. You can add a few and mix and match. One LoRA, one LyCON, etc.
---
### LoRA Rescale
Change `<lora:my_lora:4.6>` to `<lora:my_lora:1.0>` or whatever you want with the same effect.
A tool for rescaling a LoRA's weights. Should would with LoCON as well, but I have not tested it.
It all runs off a config file, which you can find an example of in `config/examples/mod_lora_scale.yml`.
Just copy that file, into the `config` folder, and rename it to `whatever_you_want.yml`.
Then you can edit the file to your liking. and call it like so:
```bash
python3 run.py config/whatever_you_want.yml
```
You can also put a full path to a config file, if you want to keep it somewhere else.
```bash
python3 run.py "/home/user/whatever_you_want.yml"
```
More notes on how it works are available in the example config file itself. This is useful when making
all LoRAs, as the ideal weight is rarely 1.0, but now you can fix that. For sliders, they can have weird scales form -2 to 2
or even -15 to 15. This will allow you to dile it in so they all have your desired scale
---
### LoRA Slider Trainer
@@ -108,13 +135,32 @@ Just went in and out. It is much worse on smaller faces than shown here.
## TODO
- [X] Add proper regs on sliders
- [ ] Add SDXL support (base model only for now)
- [X] Add SDXL support (base model only for now)
- [ ] Add plain erasing
- [ ] Make Textual inversion network trainer (network that spits out TI embeddings)
---
## Change Log
#### 2021-08-01
Major changes and update. New LoRA rescale tool, look above for details. Added better metadata so
Automatic1111 knows what the base model is. Added some experiments and a ton of updates. This thing is still unstable
at the moment, so hopefully there are not breaking changes.
Unfortunately, I am too lazy to write a proper changelog with all the changes.
I added SDXL training to sliders... but.. it does not work properly.
The slider training relies on a model's ability to understand that an unconditional (negative prompt)
means you do not want that concept in the output. SDXL does not understand this for whatever reason,
which makes separating out
concepts within the model hard. I am sure the community will find a way to fix this
over time, but for now, it is not
going to work properly. And if any of you are thinking "Could we maybe fix it by adding 1 or 2 more text
encoders to the model as well as a few more entirely separate diffusion networks?" No. God no. It just needs a little
training without every experimental new paper added to it. The KISS principal.
#### 2021-07-30
Added "anchors" to the slider trainer. This allows you to set a prompt that will be used as a
regularizer. You can set the network multiplier to force spread consistency at high weights