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Option for using fp16 weight when apply lora

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Kohaku-Blueleaf
2023-11-21 19:59:34 +08:00
parent b2e039d07b
commit 370a77f8e7
4 changed files with 25 additions and 7 deletions
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modules/shared_options.py
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@@ -201,6 +201,7 @@ options_templates.update(options_section(('optimizations', "Optimizations"), {
"persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("do not recalculate conds from prompts if prompts have not changed since previous calculation"),
"batch_cond_uncond": OptionInfo(True, "Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond comandline argument"),
"fp8_storage": OptionInfo("Disable", "FP8 weight", gr.Dropdown, {"choices": ["Disable", "Enable for SDXL", "Enable"]}).info("Use FP8 to store Linear/Conv layers' weight. Require pytorch>=2.1.0."),
"cache_fp16_weight": OptionInfo(False, "Cache FP16 weight for LoRA").info("Cache fp16 weight when enabling FP8, will increase the quality of LoRA. Use more system ram."),
}))
options_templates.update(options_section(('compatibility', "Compatibility"), {