Diffusers documentation


Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started


Schedulers from SchedulerMixin and models from ModelMixin inherit from ConfigMixin which stores all the parameters that are passed to their respective __init__ methods in a JSON-configuration file.

To use private or gated models, log-in with huggingface-cli login.


class diffusers.ConfigMixin

< >

( )

Base class for all configuration classes. All configuration parameters are stored under self.config. Also provides the from_config() and save_config() methods for loading, downloading, and saving classes that inherit from ConfigMixin.

Class attributes:

  • config_name (str) — A filename under which the config should stored when calling save_config() (should be overridden by parent class).
  • ignore_for_config (List[str]) — A list of attributes that should not be saved in the config (should be overridden by subclass).
  • has_compatibles (bool) — Whether the class has compatible classes (should be overridden by subclass).
  • _deprecated_kwargs (List[str]) — Keyword arguments that are deprecated. Note that the init function should only have a kwargs argument if at least one argument is deprecated (should be overridden by subclass).


< >

( pretrained_model_name_or_path: Union return_unused_kwargs = False return_commit_hash = False **kwargs ) dict


  • pretrained_model_name_or_path (str or os.PathLike, optional) — Can be either:

    • A string, the model id (for example google/ddpm-celebahq-256) of a pretrained model hosted on the Hub.
    • A path to a directory (for example ./my_model_directory) containing model weights saved with save_config().
  • cache_dir (Union[str, os.PathLike], optional) — Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not used.
  • force_download (bool, optional, defaults to False) — Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.
  • resume_download (bool, optional, defaults to False) — Whether or not to resume downloading the model weights and configuration files. If set to False, any incompletely downloaded files are deleted.
  • proxies (Dict[str, str], optional) — A dictionary of proxy servers to use by protocol or endpoint, for example, {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request.
  • output_loading_info(bool, optional, defaults to False) — Whether or not to also return a dictionary containing missing keys, unexpected keys and error messages.
  • local_files_only (bool, optional, defaults to False) — Whether to only load local model weights and configuration files or not. If set to True, the model won’t be downloaded from the Hub.
  • token (str or bool, optional) — The token to use as HTTP bearer authorization for remote files. If True, the token generated from diffusers-cli login (stored in ~/.huggingface) is used.
  • revision (str, optional, defaults to "main") — The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier allowed by Git.
  • subfolder (str, optional, defaults to "") — The subfolder location of a model file within a larger model repository on the Hub or locally.
  • return_unused_kwargs (bool, optional, defaults to `False) — Whether unused keyword arguments of the config are returned.
  • return_commit_hash (bool, optional, defaults to False) -- Whether the commit_hash` of the loaded configuration are returned.



A dictionary of all the parameters stored in a JSON configuration file.

Load a model or scheduler configuration.


< >

( config: Union = None return_unused_kwargs = False **kwargs ) ModelMixin or SchedulerMixin


  • config (Dict[str, Any]) — A config dictionary from which the Python class is instantiated. Make sure to only load configuration files of compatible classes.
  • return_unused_kwargs (bool, optional, defaults to False) — Whether kwargs that are not consumed by the Python class should be returned or not.
  • kwargs (remaining dictionary of keyword arguments, optional) — Can be used to update the configuration object (after it is loaded) and initiate the Python class. **kwargs are passed directly to the underlying scheduler/model’s __init__ method and eventually overwrite the same named arguments in config.


ModelMixin or SchedulerMixin

A model or scheduler object instantiated from a config dictionary.

Instantiate a Python class from a config dictionary.


>>> from diffusers import DDPMScheduler, DDIMScheduler, PNDMScheduler

>>> # Download scheduler from huggingface.co and cache.
>>> scheduler = DDPMScheduler.from_pretrained("google/ddpm-cifar10-32")

>>> # Instantiate DDIM scheduler class with same config as DDPM
>>> scheduler = DDIMScheduler.from_config(scheduler.config)

>>> # Instantiate PNDM scheduler class with same config as DDPM
>>> scheduler = PNDMScheduler.from_config(scheduler.config)


< >

( save_directory: Union push_to_hub: bool = False **kwargs )


  • save_directory (str or os.PathLike) — Directory where the configuration JSON file is saved (will be created if it does not exist).
  • push_to_hub (bool, optional, defaults to False) — Whether or not to push your model to the Hugging Face Hub after saving it. You can specify the repository you want to push to with repo_id (will default to the name of save_directory in your namespace).
  • kwargs (Dict[str, Any], optional) — Additional keyword arguments passed along to the push_to_hub() method.

Save a configuration object to the directory specified in save_directory so that it can be reloaded using the from_config() class method.


< >

( json_file_path: Union )


  • json_file_path (str or os.PathLike) — Path to the JSON file to save a configuration instance’s parameters.

Save the configuration instance’s parameters to a JSON file.


< >

( ) str



String containing all the attributes that make up the configuration instance in JSON format.

Serializes the configuration instance to a JSON string.