| Single files Diffusers supports loading pretrained pipeline (or model) weights stored in a single file, such as a ckpt or safetensors file. These single file types are typically produced from community trained models. There are three classes for loading single file weights: FromSingleFileMixin supports loading pretrained pipeline weights stored in a single file, which can either be a ckpt or safetensors file. FromOriginalVAEMixin supports loading a pretrained AutoencoderKL from pretrained ControlNet weights stored in a single file, which can either be a ckpt or safetensors file. FromOriginalControlnetMixin supports loading pretrained ControlNet weights stored in a single file, which can either be a ckpt or safetensors file. To learn more about how to load single file weights, see the Load different Stable Diffusion formats loading guide. FromSingleFileMixin class diffusers.loaders.FromSingleFileMixin < source > ( ) Load model weights saved in the .ckpt format into a DiffusionPipeline. from_single_file < source > ( pretrained_model_link_or_path **kwargs ) 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. 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. use_safetensors (bool, optional, defaults to None) — | |
| If set to None, the safetensors weights are downloaded if they’re available and if the | |
| safetensors library is installed. If set to True, the model is forcibly loaded from safetensors | |
| weights. If set to False, safetensors weights are not loaded. extract_ema (bool, optional, defaults to False) — | |
| Whether to extract the EMA weights or not. Pass True to extract the EMA weights which usually yield | |
| higher quality images for inference. Non-EMA weights are usually better for continuing finetuning. upcast_attention (bool, optional, defaults to None) — | |
| Whether the attention computation should always be upcasted. 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. prediction_type (str, optional) — | |
| The prediction type the model was trained on. Use 'epsilon' for all Stable Diffusion v1 models and | |
| the Stable Diffusion v2 base model. Use 'v_prediction' for Stable Diffusion v2. num_in_channels (int, optional, defaults to None) — | |
| The number of input channels. If None, it is automatically inferred. scheduler_type (str, optional, defaults to "pndm") — | |
| Type of scheduler to use. Should be one of ["pndm", "lms", "heun", "euler", "euler-ancestral", "dpm", "ddim"]. load_safety_checker (bool, optional, defaults to True) — | |
| Whether to load the safety checker or not. text_encoder (CLIPTextModel, optional, defaults to None) — | |
| An instance of CLIPTextModel to use, specifically the | |
| clip-vit-large-patch14 variant. If this | |
| parameter is None, the function loads a new instance of CLIPTextModel by itself if needed. vae (AutoencoderKL, optional, defaults to None) — | |
| Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations. If | |
| this parameter is None, the function will load a new instance of [CLIP] by itself, if needed. tokenizer (CLIPTokenizer, optional, defaults to None) — | |
| An instance of CLIPTokenizer to use. If this parameter is None, the function loads a new instance | |
| of CLIPTokenizer by itself if needed. original_config_file (str) — | |
| Path to .yaml config file corresponding to the original architecture. If None, will be | |
| automatically inferred by looking for a key that only exists in SD2.0 models. 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. 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: Copied >>> 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") | |
| >>> # Enable float16 and move to GPU | |
| >>> pipeline = StableDiffusionPipeline.from_single_file( | |
| ... "https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt", | |
| ... torch_dtype=torch.float16, | |
| ... ) | |
| >>> pipeline.to("cuda") FromOriginalVAEMixin class diffusers.loaders.FromOriginalVAEMixin < source > ( ) Load pretrained ControlNet weights saved in the .ckpt or .safetensors format into an AutoencoderKL. from_single_file < source > ( pretrained_model_link_or_path **kwargs ) 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. 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. use_safetensors (bool, optional, defaults to None) — | |
| If set to None, the safetensors weights are downloaded if they’re available and if the | |
| safetensors library is installed. If set to True, the model is forcibly loaded from safetensors | |
| weights. If set to False, safetensors weights are not loaded. upcast_attention (bool, optional, defaults to None) — | |
| Whether the attention computation should always be upcasted. 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. Instantiate a AutoencoderKL from pretrained ControlNet weights saved in the original .ckpt or | |
| .safetensors format. The pipeline is set in evaluation mode (model.eval()) by default. Make sure to pass both image_size and scaling_factor to from_single_file() if you’re loading | |
| a VAE from SDXL or a Stable Diffusion v2 model or higher. Examples: Copied from diffusers import AutoencoderKL | |
| url = "https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors" # can also be local file | |
| model = AutoencoderKL.from_single_file(url) FromOriginalControlnetMixin class diffusers.loaders.FromOriginalControlnetMixin < source > ( ) Load pretrained ControlNet weights saved in the .ckpt or .safetensors format into a ControlNetModel. from_single_file < source > ( pretrained_model_link_or_path **kwargs ) 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. 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. use_safetensors (bool, optional, defaults to None) — | |
| If set to None, the safetensors weights are downloaded if they’re available and if the | |
| safetensors library is installed. If set to True, the model is forcibly loaded from safetensors | |
| weights. If set to False, safetensors weights are not loaded. 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. Instantiate a ControlNetModel from pretrained ControlNet weights saved in the original .ckpt or | |
| .safetensors format. The pipeline is set in evaluation mode (model.eval()) by default. Examples: Copied from diffusers import StableDiffusionControlNetPipeline, ControlNetModel | |
| url = "https://huggingface.co/lllyasviel/ControlNet-v1-1/blob/main/control_v11p_sd15_canny.pth" # can also be a local path | |
| model = ControlNetModel.from_single_file(url) | |
| url = "https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned.safetensors" # can also be a local path | |
| pipe = StableDiffusionControlNetPipeline.from_single_file(url, controlnet=controlnet) | |