Parameters

• pretrained_model_link_or_path (str or os.PathLike, optional) — Can be either:
  • A link to the .ckpt file (for example "https://huggingface.co/<repo_id>/blob/main/<path_to_file>.ckpt") on the Hub.
  • A path to a file containing all pipeline weights.
• torch_dtype (str or torch.dtype, optional) — Override the default torch.dtype and load the model with another dtype.
• 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.
• 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.
• 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.
• 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.
• original_config_file (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.
• model_type (str, optional) — The type of model to load. If not provided, the model type will be inferred from the checkpoint file.
• image_size (int, optional) — The size of the image output. It’s used to configure the sample_size parameter of the UNet and VAE model.
• load_safety_checker (bool, optional, defaults to False) — Whether to load the safety checker model or not. By default, the safety checker is not loaded unless a safety_checker component is passed to the kwargs.
• num_in_channels (int, optional) — Specify the number of input channels for the UNet model. Read more about how to configure UNet model with this parameter here.
• scaling_factor (float, optional) — The scaling factor to use for the VAE model. If not provided, it is inferred from the config file first. If the scaling factor is not found in the config file, the default value 0.18215 is used.
• scheduler_type (str, optional) — The type of scheduler to load. If not provided, the scheduler type will be inferred from the checkpoint file.
• prediction_type (str, optional) — The type of prediction to load. If not provided, the prediction type will be inferred from the checkpoint file.
• kwargs (remaining dictionary of keyword arguments, optional) — Can be used to overwrite load and saveable variables (the pipeline components of the specific pipeline class). The overwritten components are passed directly to the pipelines __init__ method. See example below for more information.

Parameters

• pretrained_model_link_or_path (str or os.PathLike, optional) — Can be either:
  • A link to the .ckpt file (for example "https://huggingface.co/<repo_id>/blob/main/<path_to_file>.ckpt") on the Hub.
  • A path to a file containing all pipeline weights.
• config_file (str, optional) — Filepath to the configuration YAML file associated with the model. If not provided it will default to: https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml
• torch_dtype (str or torch.dtype, optional) — Override the default torch.dtype and load the model with another dtype. If "auto" is passed, the dtype is automatically derived from the model’s weights.
• 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.
• 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.
• 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.
• 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.
• image_size (int, optional, defaults to 512) — The image size the model was trained on. Use 512 for all Stable Diffusion v1 models and the Stable Diffusion v2 base model. Use 768 for Stable Diffusion v2.
• scaling_factor (float, optional, defaults to 0.18215) — The component-wise standard deviation of the trained latent space computed using the first batch of the training set. This is used to scale the latent space to have unit variance when training the diffusion model. The latents are scaled with the formula z = z * scaling_factor before being passed to the diffusion model. When decoding, the latents are scaled back to the original scale with the formula: z = 1 / scaling_factor * z. For more details, refer to sections 4.3.2 and D.1 of the High-Resolution Image Synthesis with Latent Diffusion Models paper.
• kwargs (remaining dictionary of keyword arguments, optional) — Can be used to overwrite load and saveable variables (for example the pipeline components of the specific pipeline class). The overwritten components are directly passed to the pipelines __init__ method. See example below for more information.

Parameters

• pretrained_model_link_or_path (str or os.PathLike, optional) — Can be either:
  • A link to the .ckpt file (for example "https://huggingface.co/<repo_id>/blob/main/<path_to_file>.ckpt") on the Hub.
  • A path to a file containing all pipeline weights.
• config_file (str, optional) — Filepath to the configuration YAML file associated with the model. If not provided it will default to: https://raw.githubusercontent.com/lllyasviel/ControlNet/main/models/cldm_v15.yaml
• torch_dtype (str or torch.dtype, optional) — Override the default torch.dtype and load the model with another dtype. If "auto" is passed, the dtype is automatically derived from the model’s weights.
• 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.
• 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.
• 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.
• 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.
• image_size (int, optional, defaults to 512) — The image size the model was trained on. Use 512 for all Stable Diffusion v1 models and the Stable Diffusion v2 base model. Use 768 for Stable Diffusion v2.
• upcast_attention (bool, optional, defaults to None) — Whether the attention computation should always be upcasted.
• kwargs (remaining dictionary of keyword arguments, optional) — Can be used to overwrite load and saveable variables (for example the pipeline components of the specific pipeline class). The overwritten components are directly passed to the pipelines __init__ method. See example below for more information.