# KN

<figure><img src="https://3121926949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FK2Vdw69n5ipoU5KHLczg%2Fuploads%2Fqku3V0lCBxPrN4b2Lao1%2Fb1f320d6d4a607d93aaf078e8cc2a2e.png?alt=media&#x26;token=103a92a5-d09c-4f23-b971-8c3a1da18155" alt=""><figcaption><p>Knowledge Neurons in Pretrained Transformers</p></figcaption></figure>

### apply\_kn\_to\_model-> _PreTrainedModel_

> Main function: Given the request, it applies mend to your model. Return the changed weights of the model.

```python
def apply_kn_to_model(
    model,
    tok: AutoTokenizer,
    request: List[Dict],
    hparams: KNHyperParams,
    copy=False,
    return_orig_weights=False,
    keep_original_weight=True,
    **kwargs
)
```

* **Paramters**
  * model(<mark style="color:purple;">PreTrainedModel</mark>): model to be edited
  * tok(<mark style="color:purple;">PreTrainedTokenizer</mark>): tokenizer for inputs
  * requests(<mark style="color:purple;">List\[Dict]</mark>): The edit descriptors and targets.
  * hparams(<mark style="color:purple;">Hyperparams</mark>): hyperparameters for editing method
  * copy(<mark style="color:purple;">bool</mark>): whether to copy original model
  * return\_orig\_weights(<mark style="color:purple;">bool</mark>): whether to return the weights of original model
  * keep\_original\_weight(<mark style="color:purple;">bool</mark>): whether to edit sequentially
    * `False`: edit sequentially(because the original weight is not maintained after each edit)
    * `True`: not edit sequentially
* **Return Type**
  * edited\_model(<mark style="color:purple;">PreTrainedModel</mark>): model weights after editing



### Example

```python
editor = BaseEditor.from_hparams(hparams)
prompts = ['What university did Watts Humphrey attend?',
    'Which family does Ramalinaceae belong to',
    'What role does Denny Herzig play in football?'
]
target_new = ['University of Michigan',
    'Lamiinae',
    'winger'
]
metrics, edited_model, _ = editor.edit(
    prompts=prompts,
    target_new=target_new,
    keep_original_weight=True
)
```

###
