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AutoPipeline

The AutoPipeline automatically retrieves relevant diffusers pipeline models, including the weights, configurations, and vocabularies, based on their names or paths. This lets you load and use a model without specifying its exact architecture.

Key Classes

Supported Pipelines

  • Text2Image
Model Model Architecture AutoPipeline
Stable Diffusion StableDiffusionPipeline RBLNAutoPipelineForText2Image
Stable Diffusion + LoRA StableDiffusionPipeline RBLNAutoPipelineForText2Image
Stable Diffusion V3† StableDiffusion3Pipeline RBLNAutoPipelineForText2Image
Stable Diffusion XL StableDiffusionXLPipeline RBLNAutoPipelineForText2Image
Stable Diffusion XL + multi-LoRA StableDiffusionXLPipeline RBLNAutoPipelineForText2Image
SDXL-turbo StableDiffusionXLPipeline RBLNAutoPipelineForText2Image
Stable Diffusion + ControlNet StableDiffusionControlNetPipeline RBLNAutoPipelineForText2Image
Stable Diffusion XL + ControlNet StableDiffusionXLControlNetPipeline RBLNAutoPipelineForText2Image
Kandinsky V2.2 KandinskyV22CombinedPipeline RBLNAutoPipelineForText2Image
  • Image2Image
Model Model Architecture AutoPipeline
Stable Diffusion StableDiffusionImg2ImgPipeline RBLNAutoPipelineForImage2Image
Stable Diffusion V3† StableDiffusion3Img2ImgPipeline RBLNAutoPipelineForImage2Image
Stable Diffusion XL StableDiffusionXLImg2ImgPipeline RBLNAutoPipelineForImage2Image
SDXL-turbo StableDiffusionXLImg2ImgPipeline RBLNAutoPipelineForImage2Image
Stable Diffusion + ControlNet StableDiffusionControlNetImg2ImgPipeline RBLNAutoPipelineForImage2Image
Stable Diffusion XL + ControlNet StableDiffusionXLControlNetImg2ImgPipeline RBLNAutoPipelineForImage2Image
Kandinsky V2.2 KandinskyV22Img2ImgCombinedPipeline RBLNAutoPipelineForImage2Image
  • Inpainting
Model Model Architecture AutoPipeline
Stable Diffusion StableDiffusionInpaintPipeline RBLNAutoPipelineForInpainting
Stable Diffusion V3† StableDiffusion3InpaintPipeline RBLNAutoPipelineForInpainting
Stable Diffusion XL StableDiffusionXLInpaintPipeline RBLNAutoPipelineForInpainting
Kandinsky V2.2 KandinskyV22InpaintCombinedPipeline RBLNAutoPipelineForInpainting

API Reference

RBLNAutoPipelineBase

from_pretrained(model_id, *, export=None, rbln_config=None, **kwargs) classmethod

Load an RBLN-accelerated Diffusers pipeline from a pretrained checkpoint or a compiled RBLN artifact.

This method determines the concrete RBLN* model class that corresponds to the underlying Diffusers pipeline architecture and dispatches to that class's from_pretrained() implementation. If a compiled RBLN folder is detected at model_id (or export=False is explicitly passed), it loads the compiled artifacts; otherwise it compiles from the original Diffusers checkpoint.

Parameters:

Name Type Description Default
model_id str | Path

HF repo id or local path. For compiled models, this should point to a directory (optionally under subfolder) that contains *.rbln files and rbln_config.json.

 required
export bool | None

Force compilation from a Diffusers checkpoint. When None, this is inferred by checking whether compiled artifacts exist at model_id.

 None
rbln_config dict[str, Any] | RBLNModelConfig | None

RBLN compilation/runtime configuration. May be provided as a dictionary or as an instance of the specific model's config class (e.g., RBLNFluxPipelineConfig).

 None
kwargs Any

Additional keyword arguments. - Arguments prefixed with rbln_ are forwarded to the RBLN config. - Remaining arguments are forwarded to the Diffusers loader.

 {}

Returns:

Name Type Description
RBLNBaseModel RBLNBaseModel

An instantiated RBLN model wrapping the Diffusers pipeline, ready for inference on RBLN NPUs.

register(rbln_cls, exist_ok=False) staticmethod

Register a new RBLN model class.

Parameters:

Name Type Description Default
rbln_cls type[RBLNBaseModel]

The RBLN model class to register.

 required
exist_ok bool

Whether to allow registering an already registered model.

 False

RBLNAutoPipelineForText2Image

Bases: RBLNAutoPipelineBase, AutoPipelineForText2Image

Text2Image AutoPipeline for RBLN NPUs.

from_pretrained(model_id, *, export=None, rbln_config=None, **kwargs) classmethod

Load an RBLN-accelerated Diffusers pipeline from a pretrained checkpoint or a compiled RBLN artifact.

This method determines the concrete RBLN* model class that corresponds to the underlying Diffusers pipeline architecture and dispatches to that class's from_pretrained() implementation. If a compiled RBLN folder is detected at model_id (or export=False is explicitly passed), it loads the compiled artifacts; otherwise it compiles from the original Diffusers checkpoint.

Parameters:

Name Type Description Default
model_id str | Path

HF repo id or local path. For compiled models, this should point to a directory (optionally under subfolder) that contains *.rbln files and rbln_config.json.

 required
export bool | None

Force compilation from a Diffusers checkpoint. When None, this is inferred by checking whether compiled artifacts exist at model_id.

 None
rbln_config dict[str, Any] | RBLNModelConfig | None

RBLN compilation/runtime configuration. May be provided as a dictionary or as an instance of the specific model's config class (e.g., RBLNFluxPipelineConfig).

 None
kwargs Any

Additional keyword arguments. - Arguments prefixed with rbln_ are forwarded to the RBLN config. - Remaining arguments are forwarded to the Diffusers loader.

 {}

Returns:

Name Type Description
RBLNBaseModel RBLNBaseModel

An instantiated RBLN model wrapping the Diffusers pipeline, ready for inference on RBLN NPUs.

register(rbln_cls, exist_ok=False) staticmethod

Register a new RBLN model class.

Parameters:

Name Type Description Default
rbln_cls type[RBLNBaseModel]

The RBLN model class to register.

 required
exist_ok bool

Whether to allow registering an already registered model.

 False

RBLNAutoPipelineForImage2Image

Bases: RBLNAutoPipelineBase, AutoPipelineForImage2Image

Image2Image AutoPipeline for RBLN NPUs.

from_pretrained(model_id, *, export=None, rbln_config=None, **kwargs) classmethod

Load an RBLN-accelerated Diffusers pipeline from a pretrained checkpoint or a compiled RBLN artifact.

This method determines the concrete RBLN* model class that corresponds to the underlying Diffusers pipeline architecture and dispatches to that class's from_pretrained() implementation. If a compiled RBLN folder is detected at model_id (or export=False is explicitly passed), it loads the compiled artifacts; otherwise it compiles from the original Diffusers checkpoint.

Parameters:

Name Type Description Default
model_id str | Path

HF repo id or local path. For compiled models, this should point to a directory (optionally under subfolder) that contains *.rbln files and rbln_config.json.

 required
export bool | None

Force compilation from a Diffusers checkpoint. When None, this is inferred by checking whether compiled artifacts exist at model_id.

 None
rbln_config dict[str, Any] | RBLNModelConfig | None

RBLN compilation/runtime configuration. May be provided as a dictionary or as an instance of the specific model's config class (e.g., RBLNFluxPipelineConfig).

 None
kwargs Any

Additional keyword arguments. - Arguments prefixed with rbln_ are forwarded to the RBLN config. - Remaining arguments are forwarded to the Diffusers loader.

 {}

Returns:

Name Type Description
RBLNBaseModel RBLNBaseModel

An instantiated RBLN model wrapping the Diffusers pipeline, ready for inference on RBLN NPUs.

register(rbln_cls, exist_ok=False) staticmethod

Register a new RBLN model class.

Parameters:

Name Type Description Default
rbln_cls type[RBLNBaseModel]

The RBLN model class to register.

 required
exist_ok bool

Whether to allow registering an already registered model.

 False

RBLNAutoPipelineForInpainting

Bases: RBLNAutoPipelineBase, AutoPipelineForInpainting

Inpainting AutoPipeline for RBLN NPUs.

from_pretrained(model_id, *, export=None, rbln_config=None, **kwargs) classmethod

Load an RBLN-accelerated Diffusers pipeline from a pretrained checkpoint or a compiled RBLN artifact.

This method determines the concrete RBLN* model class that corresponds to the underlying Diffusers pipeline architecture and dispatches to that class's from_pretrained() implementation. If a compiled RBLN folder is detected at model_id (or export=False is explicitly passed), it loads the compiled artifacts; otherwise it compiles from the original Diffusers checkpoint.

Parameters:

Name Type Description Default
model_id str | Path

HF repo id or local path. For compiled models, this should point to a directory (optionally under subfolder) that contains *.rbln files and rbln_config.json.

 required
export bool | None

Force compilation from a Diffusers checkpoint. When None, this is inferred by checking whether compiled artifacts exist at model_id.

 None
rbln_config dict[str, Any] | RBLNModelConfig | None

RBLN compilation/runtime configuration. May be provided as a dictionary or as an instance of the specific model's config class (e.g., RBLNFluxPipelineConfig).

 None
kwargs Any

Additional keyword arguments. - Arguments prefixed with rbln_ are forwarded to the RBLN config. - Remaining arguments are forwarded to the Diffusers loader.

 {}

Returns:

Name Type Description
RBLNBaseModel RBLNBaseModel

An instantiated RBLN model wrapping the Diffusers pipeline, ready for inference on RBLN NPUs.

register(rbln_cls, exist_ok=False) staticmethod

Register a new RBLN model class.

Parameters:

Name Type Description Default
rbln_cls type[RBLNBaseModel]

The RBLN model class to register.

 required
exist_ok bool

Whether to allow registering an already registered model.

 False