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config: typing.Union[diffusers.configuration_utils.FrozenDict, typing.Dict[str, typing.Any]] = None |
return_unused_kwargs = False |
**kwargs |
) |
Parameters |
config (Dict[str, Any]) — |
A config dictionary from which the Python class will be 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 being loaded) and initiate the Python class. |
**kwargs will be directly passed to the underlying scheduler/model’s __init__ method and eventually |
overwrite same named arguments of config. |
Instantiate a Python class from a config dictionary |
Examples: |
Copied |
>>> 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) |
load_config |
< |
source |
> |
( |
pretrained_model_name_or_path: typing.Union[str, os.PathLike] |
return_unused_kwargs = False |
**kwargs |
) |
Parameters |
pretrained_model_name_or_path (str or os.PathLike, optional) — |
Can be either: |
A string, the model id of a model repo on huggingface.co. Valid model ids should have an |
organization name, like google/ddpm-celebahq-256. |
A path to a directory containing model weights saved using save_config(), e.g., |
./my_model_directory/. |
cache_dir (Union[str, os.PathLike], optional) — |
Path to a directory in which a downloaded pretrained model configuration should be cached if the |
standard cache should not be 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 delete incompletely received files. Will attempt to resume the download if such a |
file exists. |
proxies (Dict[str, str], optional) — |
A dictionary of proxy servers to use by protocol or endpoint, e.g., {'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 or not to only look at local files (i.e., do not try to download the model). |
use_auth_token (str or bool, optional) — |
The token to use as HTTP bearer authorization for remote files. If True, will use the token generated |
when running transformers-cli login (stored in ~/.huggingface). |
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