| # LoRA interrogate script by @bdsqlsz | |
| $v2 = 0 # load Stable Diffusion v2.x model / Stable Diffusion 2.x模型读取 | |
| $sd_model = "./sd-models/sd_model.safetensors" # Stable Diffusion model to load: ckpt or safetensors file | 读取的基础SD模型, 保存格式 cpkt 或 safetensors | |
| $model = "./output/LoRA.safetensors" # LoRA model to interrogate: ckpt or safetensors file | 需要调查关键字的LORA模型, 保存格式 cpkt 或 safetensors | |
| $batch_size = 64 # batch size for processing with Text Encoder | 使用 Text Encoder 处理时的批量大小，默认16，推荐64/128 | |
| $clip_skip = 1 # use output of nth layer from back of text encoder (n>=1) | 使用文本编码器倒数第 n 层的输出，n 可以是大于等于 1 的整数 | |
| # Activate python venv | |
| .\venv\Scripts\activate | |
| $Env:HF_HOME = "huggingface" | |
| $ext_args = [System.Collections.ArrayList]::new() | |
| if ($v2) { | |
| [void]$ext_args.Add("--v2") | |
| } | |
| # run interrogate | |
| accelerate launch --num_cpu_threads_per_process=8 "./scripts/networks/lora_interrogator.py" ` | |
| --sd_model=$sd_model ` | |
| --model=$model ` | |
| --batch_size=$batch_size ` | |
| --clip_skip=$clip_skip ` | |
| $ext_args | |
| Write-Output "Interrogate finished" | |
| Read-Host | Out-Null ; | |