diff --git a/src/diffusers/loaders.py b/src/diffusers/loaders.py index f41d0ffe72e3..c03d72085e93 100644 --- a/src/diffusers/loaders.py +++ b/src/diffusers/loaders.py @@ -1205,10 +1205,10 @@ def from_ckpt(cls, pretrained_model_link_or_path, **kwargs): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. - use_safetensors (`bool`, *optional* ): - If set to `True`, the pipeline will be loaded from `safetensors` weights. If set to `None` (the - default). The pipeline will load using `safetensors` if the safetensors weights are available *and* if - `safetensors` is installed. If the to `False` the pipeline will *not* use `safetensors`. + use_safetensors (`bool`, *optional*, defaults to `None`): + If set to `None`, the pipeline will load the `safetensors` weights if they're available **and** if the + `safetensors` library is installed. If set to `True`, the pipeline will forcibly load the models from + `safetensors` weights. If set to `False` the pipeline will *not* use `safetensors`. extract_ema (`bool`, *optional*, defaults to `False`): Only relevant for checkpoints that have both EMA and non-EMA weights. Whether to extract the EMA weights or not. Defaults to `False`. Pass `True` to extract the EMA weights. EMA weights usually yield higher quality images for diff --git a/src/diffusers/models/modeling_utils.py b/src/diffusers/models/modeling_utils.py index 6644042077d2..ef14ec3d09ef 100644 --- a/src/diffusers/models/modeling_utils.py +++ b/src/diffusers/models/modeling_utils.py @@ -406,10 +406,10 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P variant (`str`, *optional*): If specified load weights from `variant` filename, *e.g.* pytorch_model..bin. `variant` is ignored when using `from_flax`. - use_safetensors (`bool`, *optional* ): - If set to `True`, the pipeline will forcibly load the models from `safetensors` weights. If set to - `None` (the default). The pipeline will load using `safetensors` if safetensors weights are available - *and* if `safetensors` is installed. If the to `False` the pipeline will *not* use `safetensors`. + use_safetensors (`bool`, *optional*, defaults to `None`): + If set to `None`, the `safetensors` weights will be downloaded if they're available **and** if the + `safetensors` library is installed. If set to `True`, the model will be forcibly loaded from + `safetensors` weights. If set to `False`, loading will *not* use `safetensors`. diff --git a/src/diffusers/pipelines/pipeline_utils.py b/src/diffusers/pipelines/pipeline_utils.py index 82bcda54938d..9288248d309b 100644 --- a/src/diffusers/pipelines/pipeline_utils.py +++ b/src/diffusers/pipelines/pipeline_utils.py @@ -814,10 +814,10 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P also tries to not use more than 1x model size in CPU memory (including peak memory) while loading the model. This is only supported when torch version >= 1.9.0. If you are using an older version of torch, setting this argument to `True` will raise an error. - use_safetensors (`bool`, *optional* ): - If set to `True`, the pipeline will be loaded from `safetensors` weights. If set to `None` (the - default). The pipeline will load using `safetensors` if the safetensors weights are available *and* if - `safetensors` is installed. If the to `False` the pipeline will *not* use `safetensors`. + use_safetensors (`bool`, *optional*, defaults to `None`): + If set to `None`, the pipeline will load the `safetensors` weights if they're available **and** if the + `safetensors` library is installed. If set to `True`, the pipeline will forcibly load the models from + `safetensors` weights. If set to `False` the pipeline will *not* use `safetensors`. kwargs (remaining dictionary of keyword arguments, *optional*): Can be used to overwrite load - and saveable variables - *i.e.* the pipeline components - of the specific pipeline class. The overwritten components are then directly passed to the pipelines