The from_single_file() method allows you to load:
Read the Model files and layouts guide to learn more about the Diffusers-multifolder layout versus the single-file layout, and how to load models stored in these different layouts.
StableCascadeUNetLoad model weights saved in the .ckpt format into a DiffusionPipeline.
( pretrained_model_link_or_path **kwargs )
Parameters
str or os.PathLike, optional) —
Can be either:
.ckpt file (for example
"https://huggingface.co/<repo_id>/blob/main/<path_to_file>.ckpt") on the Hub.str or torch.dtype, optional) —
Override the default torch.dtype and load the model with another dtype. 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. Union[str, os.PathLike], optional) —
Path to a directory where a downloaded pretrained model configuration is cached if the standard cache
is not used. 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. 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. 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. 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. str, optional) —
The path to the original config file that was used to train the model. If not provided, the config file
will be inferred from the checkpoint file. str, optional) —
Can be either:
CompVis/ldm-text2im-large-256) of a pretrained pipeline
hosted on the Hub../my_pipeline_directory/) containing the pipeline
component configs in Diffusers format.__init__ method. See example
below for more information. Instantiate a DiffusionPipeline from pretrained pipeline weights saved in the .ckpt or .safetensors
format. The pipeline is set in evaluation mode (model.eval()) by default.
Examples:
>>> from diffusers import StableDiffusionPipeline
>>> # Download pipeline from huggingface.co and cache.
>>> pipeline = StableDiffusionPipeline.from_single_file(
... "https://huggingface.co/WarriorMama777/OrangeMixs/blob/main/Models/AbyssOrangeMix/AbyssOrangeMix.safetensors"
... )
>>> # Download pipeline from local file
>>> # file is downloaded under ./v1-5-pruned-emaonly.ckpt
>>> pipeline = StableDiffusionPipeline.from_single_file("./v1-5-pruned-emaonly.ckpt")
>>> # Enable float16 and move to GPU
>>> pipeline = StableDiffusionPipeline.from_single_file(
... "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt",
... torch_dtype=torch.float16,
... )
>>> pipeline.to("cuda")Load pretrained weights saved in the .ckpt or .safetensors format into a model.
( pretrained_model_link_or_path_or_dict: typing.Optional[str] = None **kwargs )
Parameters
str, optional) —
Can be either:
.safetensors or .ckpt file (for example
"https://huggingface.co/<repo_id>/blob/main/<path_to_file>.safetensors") on the Hub.str, optional) —
CompVis/ldm-text2im-large-256) of a pretrained pipeline hosted
on the Hub../my_pipeline_directory/) containing the pipeline component
configs in Diffusers format.str, optional, defaults to "") —
The subfolder location of a model file within a larger model repository on the Hub or locally. str, optional) —
Dict or path to a yaml file containing the configuration for the model in its original format.
If a dict is provided, it will be used to initialize the model configuration. torch.dtype, optional) —
Override the default torch.dtype and load the model with another dtype. 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. Union[str, os.PathLike], optional) —
Path to a directory where a downloaded pretrained model configuration is cached if the standard cache
is not used. 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. 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. 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. 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. bool, optional, defaults to True if torch version >= 1.9.0 and —
is_accelerate_available() else False): Speed up model loading only loading the pretrained weights and
not initializing the weights. This also tries to not use more than 1x model size in CPU memory
(including peak memory) while loading the model. Only supported for PyTorch >= 1.9.0. If you are using
an older version of PyTorch, setting this argument to True will raise an error. __init__
method. See example below for more information. Instantiate a model from pretrained weights saved in the original .ckpt or .safetensors format. The model
is set in evaluation mode (model.eval()) by default.