#
Guiders

Classifier-free guidance steers model generation that better match a prompt and is commonly used to improve generation quality, control, and adherence to prompts. There are different types of guidance methods, and in Diffusers, they are known as guiders. Like blocks, it is easy to switch and use different guiders for different use cases without rewriting the pipeline.

This guide will show you how to switch guiders, adjust guider parameters, and load and share them to the Hub.

##
Switching guiders

ClassifierFreeGuidance is the default guider and created when a pipeline is initialized with init_pipeline(). It is created by `from_config` which means it doesn’t require loading specifications from a modular repository. A guider won’t be listed in `modular_model_index.json`.

Use get_component_spec() to inspect a guider.

    t2i_pipeline.get_component_spec("guider")
    ComponentSpec(name='guider', type_hint=<class 'diffusers.guiders.classifier_free_guidance.ClassifierFreeGuidance'>, description=None, config=FrozenDict([('guidance_scale', 7.5), ('guidance_rescale', 0.0), ('use_original_formulation', False), ('start', 0.0), ('stop', 1.0), ('_use_default_values', ['start', 'guidance_rescale', 'stop', 'use_original_formulation'])]), repo=None, subfolder=None, variant=None, revision=None, default_creation_method='from_config')

Switch to a different guider by passing the new guider to update_components().

Changing guiders will return text letting you know you’re changing the guider type.

    ModularPipeline.update_components: adding guider with new type: PerturbedAttentionGuidance, previous type: ClassifierFreeGuidance

    from diffusers import LayerSkipConfig, PerturbedAttentionGuidance

    config = LayerSkipConfig(indices=[2, 9], fqn="mid_block.attentions.0.transformer_blocks", skip_attention=False, skip_attention_scores=True, skip_ff=False)
    guider = PerturbedAttentionGuidance(
        guidance_scale=5.0, perturbed_guidance_scale=2.5, perturbed_guidance_config=config
    )
    t2i_pipeline.update_components(guider=guider)

Use get_component_spec() again to verify the guider type is different.

    t2i_pipeline.get_component_spec("guider")
    ComponentSpec(name='guider', type_hint=<class 'diffusers.guiders.perturbed_attention_guidance.PerturbedAttentionGuidance'>, description=None, config=FrozenDict([('guidance_scale', 5.0), ('perturbed_guidance_scale', 2.5), ('perturbed_guidance_start', 0.01), ('perturbed_guidance_stop', 0.2), ('perturbed_guidance_layers', None), ('perturbed_guidance_config', LayerSkipConfig(indices=[2, 9], fqn='mid_block.attentions.0.transformer_blocks', skip_attention=False, skip_attention_scores=True, skip_ff=False, dropout=1.0)), ('guidance_rescale', 0.0), ('use_original_formulation', False), ('start', 0.0), ('stop', 1.0), ('_use_default_values', ['perturbed_guidance_start', 'use_original_formulation', 'perturbed_guidance_layers', 'stop', 'start', 'guidance_rescale', 'perturbed_guidance_stop']), ('_class_name', 'PerturbedAttentionGuidance'), ('_diffusers_version', '0.35.0.dev0')]), repo=None, subfolder=None, variant=None, revision=None, default_creation_method='from_config')

##
Loading custom guiders

Guiders that are already saved on the Hub with a `modular_model_index.json` file are considered a `from_pretrained` component now instead of a `from_config` component.

    {
      "guider": [
        null,
        null,
        {
          "repo": "YiYiXu/modular-loader-t2i-guider",
          "revision": null,
          "subfolder": "pag_guider",
          "type_hint": [
            "diffusers",
            "PerturbedAttentionGuidance"
          ],
          "variant": null
        }
      ]
    }

The guider is only created after calling load_components() based on the loading specification in `modular_model_index.json`.

    t2i_pipeline = t2i_blocks.init_pipeline("YiYiXu/modular-doc-guider")
    # not created during init
    assert t2i_pipeline.guider is None
    t2i_pipeline.load_components()
    # loaded as PAG guider
    t2i_pipeline.guider

##
Changing guider parameters

The guider parameters can be adjusted with either the create() method or with update_components(). The example below changes the `guidance_scale` value.

create
update_components

    guider_spec = t2i_pipeline.get_component_spec("guider")
    guider = guider_spec.create(guidance_scale=10)
    t2i_pipeline.update_components(guider=guider)

##
Uploading custom guiders

Call the push_to_hub() method on a custom guider to share it to the Hub.

    guider.push_to_hub("YiYiXu/modular-loader-t2i-guider", subfolder="pag_guider")

To make this guider available to the pipeline, either modify the `modular_model_index.json` file or use the update_components() method.

modular_model_index.json
update_components

Edit the `modular_model_index.json` file and add a loading specification for the guider by pointing to a folder containing the guider config.

    {
      "guider": [
        "diffusers",
        "PerturbedAttentionGuidance",
        {
          "repo": "YiYiXu/modular-loader-t2i-guider",
          "revision": null,
          "subfolder": "pag_guider",
          "type_hint": [
            "diffusers",
            "PerturbedAttentionGuidance"
          ],
          "variant": null
        }
      ],

< > Update on GitHub