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stevhliu merged 2 commits into from
Dec 17, 2024
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[docs] delete_adapters() #10245

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delete_adapters
stevhliu Dec 16, 2024
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Merge branch 'main' into delete-adapter
sayakpaul Dec 17, 2024
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21 changes: 15 additions & 6 deletions docs/source/en/tutorials/using_peft_for_inference.md
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Expand Up @@ -56,7 +56,7 @@ image

With the `adapter_name` parameter, it is really easy to use another adapter for inference! Load the [nerijs/pixel-art-xl](https://huggingface.co/nerijs/pixel-art-xl) adapter that has been fine-tuned to generate pixel art images and call it `"pixel"`.

The pipeline automatically sets the first loaded adapter (`"toy"`) as the active adapter, but you can activate the `"pixel"` adapter with the [`~diffusers.loaders.UNet2DConditionLoadersMixin.set_adapters`] method:
The pipeline automatically sets the first loaded adapter (`"toy"`) as the active adapter, but you can activate the `"pixel"` adapter with the [`~PeftAdapterMixin.set_adapters`] method:

```python
pipe.load_lora_weights("nerijs/pixel-art-xl", weight_name="pixel-art-xl.safetensors", adapter_name="pixel")
Expand Down Expand Up @@ -85,7 +85,7 @@ By default, if the most up-to-date versions of PEFT and Transformers are detecte

You can also merge different adapter checkpoints for inference to blend their styles together.

Once again, use the [`~diffusers.loaders.UNet2DConditionLoadersMixin.set_adapters`] method to activate the `pixel` and `toy` adapters and specify the weights for how they should be merged.
Once again, use the [`~PeftAdapterMixin.set_adapters`] method to activate the `pixel` and `toy` adapters and specify the weights for how they should be merged.

```python
pipe.set_adapters(["pixel", "toy"], adapter_weights=[0.5, 1.0])
Expand Down Expand Up @@ -114,7 +114,7 @@ Impressive! As you can see, the model generated an image that mixed the characte
> [!TIP]
> Through its PEFT integration, Diffusers also offers more efficient merging methods which you can learn about in the [Merge LoRAs](../using-diffusers/merge_loras) guide!

To return to only using one adapter, use the [`~diffusers.loaders.UNet2DConditionLoadersMixin.set_adapters`] method to activate the `"toy"` adapter:
To return to only using one adapter, use the [`~PeftAdapterMixin.set_adapters`] method to activate the `"toy"` adapter:

```python
pipe.set_adapters("toy")
Expand All @@ -127,7 +127,7 @@ image = pipe(
image
```

Or to disable all adapters entirely, use the [`~diffusers.loaders.UNet2DConditionLoadersMixin.disable_lora`] method to return the base model.
Or to disable all adapters entirely, use the [`~PeftAdapterMixin.disable_lora`] method to return the base model.

```python
pipe.disable_lora()
Expand All @@ -140,7 +140,8 @@ image
![no-lora](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/peft_integration/diffusers_peft_lora_inference_20_1.png)

### Customize adapters strength
For even more customization, you can control how strongly the adapter affects each part of the pipeline. For this, pass a dictionary with the control strengths (called "scales") to [`~diffusers.loaders.UNet2DConditionLoadersMixin.set_adapters`].

For even more customization, you can control how strongly the adapter affects each part of the pipeline. For this, pass a dictionary with the control strengths (called "scales") to [`~PeftAdapterMixin.set_adapters`].

For example, here's how you can turn on the adapter for the `down` parts, but turn it off for the `mid` and `up` parts:
```python
Expand Down Expand Up @@ -195,7 +196,7 @@ image

![block-lora-mixed](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/peft_integration/diffusers_peft_lora_inference_block_mixed.png)

## Manage active adapters
## Manage adapters

You have attached multiple adapters in this tutorial, and if you're feeling a bit lost on what adapters have been attached to the pipeline's components, use the [`~diffusers.loaders.StableDiffusionLoraLoaderMixin.get_active_adapters`] method to check the list of active adapters:

Expand All @@ -212,3 +213,11 @@ list_adapters_component_wise = pipe.get_list_adapters()
list_adapters_component_wise
{"text_encoder": ["toy", "pixel"], "unet": ["toy", "pixel"], "text_encoder_2": ["toy", "pixel"]}
```

The [`~PeftAdapterMixin.delete_adapters`] function completely removes an adapter and their LoRA layers from a model.

```py
pipe.delete_adapters("toy")
pipe.get_active_adapters()
["pixel"]
```