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# LyCORIS
[LyCORIS](https://hf.co/papers/2309.14859) (Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion) are LoRA-like matrix decomposition adapters that modify the cross-attention layer of the UNet. The [LoHa](loha) and [LoKr](lokr) methods inherit from the `Lycoris` classes here.
## LycorisConfig[[peft.tuners.lycoris_utils.LycorisConfig]]
"}, {"name": "alpha_pattern", "val": ": Optional[dict] = "}]}>
A base config for LyCORIS like adapters
## LycorisLayer[[peft.tuners.lycoris_utils.LycorisLayer]]
A base layer for LyCORIS like adapters
- **safe_merge** (`bool`, *optional*) --
If `True`, the merge operation will be performed in a copy of the original weights and check for NaNs
before merging the weights. This is useful if you want to check if the merge operation will produce
NaNs. Defaults to `False`.
- **adapter_names** (`List[str]`, *optional*) --
The list of adapter names that should be merged. If `None`, all active adapters will be merged.
Defaults to `None`.
Merge the active adapter weights into the base weights
This method unmerges all merged adapter layers from the base weights.
## LycorisTuner[[peft.tuners.lycoris_utils.LycorisTuner]]
- **model** (`torch.nn.Module`) -- The model to be adapted.
- **config** ([LoraConfig](/docs/peft/pr_3219/en/package_reference/lora#peft.LoraConfig)) -- The configuration of the Lora model.
- **adapter_name** (`str`) -- The name of the adapter, defaults to `"default"`.
- **low_cpu_mem_usage** (`bool`, `optional`, defaults to `False`) --
Create empty adapter weights on meta device. Useful to speed up the loading process.
A base tuner for LyCORIS like adapters

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