# Model merge[[peft.utils.merge_utils.prune]]

PEFT provides several internal utilities for [merging LoRA adapters](../developer_guides/model_merging) with the TIES and DARE methods.

#### peft.utils.merge_utils.prune[[peft.utils.merge_utils.prune]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L75)

Prune the values of task tensors based on the `method`.

**Parameters:**

tensor (`torch.Tensor`) --The tensor to prune.

density (`float`) --The fraction of values to preserve. Should be in [0,1].

method (`str`) --The method to use to prune. Should be one of ["magnitude", "random"].

rescale (`bool`) --Whether to rescale the result to preserve the expected value of the original tensor.

**Returns:**

``torch.Tensor``

The pruned tensor.

#### peft.utils.merge_utils.calculate_majority_sign_mask[[peft.utils.merge_utils.calculate_majority_sign_mask]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L103)

Get the mask of the majority sign across the task tensors. Task tensors are stacked on dimension 0.

**Parameters:**

tensor (`torch.Tensor`) --The tensor to get the mask from.

method (`str`) --The method to use to get the mask. Should be one of ["total", "frequency"].

**Returns:**

``torch.Tensor``

The majority sign mask.

#### peft.utils.merge_utils.disjoint_merge[[peft.utils.merge_utils.disjoint_merge]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L128)

Merge the task tensors using disjoint merge.

**Parameters:**

task_tensors (`torch.Tensor`) --The task tensors to merge.

majority_sign_mask (`torch.Tensor`) --The mask of the majority sign across the task tensors.

**Returns:**

``torch.Tensor``

The merged tensor.

#### peft.utils.merge_utils.task_arithmetic[[peft.utils.merge_utils.task_arithmetic]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L144)

Merge the task tensors using `task arithmetic`.

**Parameters:**

task_tensors(`List[torch.Tensor]`) --The task tensors to merge.

weights (`torch.Tensor`) --The weights of the task tensors.

**Returns:**

``torch.Tensor``

The merged tensor.

#### peft.utils.merge_utils.ties[[peft.utils.merge_utils.ties]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L185)

Merge the task tensors using `ties`.

**Parameters:**

task_tensors(`List[torch.Tensor]`) --The task tensors to merge.

weights (`torch.Tensor`) --The weights of the task tensors.

density (`float`) --The fraction of values to preserve. Should be in [0,1].

majority_sign_method (`str`) : The method to use to get the majority sign mask. Should be one of ["total", "frequency"].

**Returns:**

``torch.Tensor``

The merged tensor.

#### peft.utils.merge_utils.dare_linear[[peft.utils.merge_utils.dare_linear]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L217)

Merge the task tensors using `dare linear`.

**Parameters:**

task_tensors(`List[torch.Tensor]`) --The task tensors to merge.

weights (`torch.Tensor`) --The weights of the task tensors.

density (`float`) --The fraction of values to preserve. Should be in [0,1].

**Returns:**

``torch.Tensor``

The merged tensor.

#### peft.utils.merge_utils.dare_ties[[peft.utils.merge_utils.dare_ties]]

[Source](https://github.com/huggingface/peft/blob/v0.19.0/src/peft/utils/merge_utils.py#L239)

Merge the task tensors using `dare ties`.

**Parameters:**

task_tensors(`List[torch.Tensor]`) --The task tensors to merge.

weights (`torch.Tensor`) --The weights of the task tensors.

density (`float`) --The fraction of values to preserve. Should be in [0,1].

majority_sign_method (`str`) : The method to use to get the majority sign mask. Should be one of ["total", "frequency"].

**Returns:**

``torch.Tensor``

The merged tensor.