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76 lines
2.4 KiB
YAML
76 lines
2.4 KiB
YAML
---
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# this is in yaml format. You can use json if you prefer
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# I like both but yaml is easier to read and write
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# plus it has comments which is nice for documentation
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job: extract # tells the runner what to do
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config:
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# the name will be used to create a folder in the output folder
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# it will also replace any [name] token in the rest of this config
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name: name_of_your_model
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# can be hugging face model, a .ckpt, or a .safetensors
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base_model: "/path/to/base/model.safetensors"
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# can be hugging face model, a .ckpt, or a .safetensors
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extract_model: "/path/to/model/to/extract/trained.safetensors"
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# we will create folder here with name above so. This will create /path/to/output/folder/name_of_your_model
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output_folder: "/path/to/output/folder"
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is_v2: false
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dtype: fp16 # saved dtype
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device: cpu # cpu, cuda:0, etc
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# processes can be chained like this to run multiple in a row
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# they must all use same models above, but great for testing different
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# sizes and typed of extractions. It is much faster as we already have the models loaded
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process:
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# process 1
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- type: locon # locon or lora (locon is lycoris)
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filename: "[name]_64_32.safetensors" # will be put in output folder
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dtype: fp16
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mode: fixed
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linear: 64
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conv: 32
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# process 2
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- type: locon
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output_path: "/absolute/path/for/this/output.safetensors" # can be absolute
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mode: ratio
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linear: 0.2
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conv: 0.2
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# process 3
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- type: locon
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filename: "[name]_ratio_02.safetensors"
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mode: quantile
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linear: 0.5
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conv: 0.5
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# process 4
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- type: lora # traditional lora extraction (lierla) with linear layers only
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filename: "[name]_4.safetensors"
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mode: fixed # fixed, ratio, quantile supported for lora as well
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linear: 4 # lora dim or rank
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# no conv for lora
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# process 5
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- type: lora
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filename: "[name]_q05.safetensors"
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mode: quantile
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linear: 0.5
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# you can put any information you want here, and it will be saved in the model
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# the below is an example. I recommend doing trigger words at a minimum
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# in the metadata. The software will include this plus some other information
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meta:
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name: "[name]" # [name] gets replaced with the name above
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description: A short description of your model
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trigger_words:
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- put
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- trigger
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- words
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- here
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version: '0.1'
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creator:
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name: Your Name
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email: your@email.com
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website: https://yourwebsite.com
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any: All meta data above is arbitrary, it can be whatever you want.
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