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