Struct ModelConfigBuilder 

pub struct ModelConfigBuilder { /* private fields */ }

Builder for ModelConfig.

Implementations

impl ModelConfigBuilder

pub fn enable_mmap<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Whether to memory-map model (default: false)

pub fn max_vram<VALUE: Into<f32>>(&mut self, value: VALUE) -> &mut Self

Maximum VRAM budget in GiB for graph-cut segmented execution. 0 disables graph splitting; -1 auto-detects free VRAM minus 1 GiB

pub fn upscale_model<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to esrgan model. Upscale images after generate, just RealESRGAN_x4plus_anime_6B supported by now

pub fn upscale_repeats<VALUE: Into<i32>>(&mut self, value: VALUE) -> &mut Self

Run the ESRGAN upscaler this many times (default 1)

pub fn upscale_tile_size<VALUE: Into<i32>>(&mut self, value: VALUE) -> &mut Self

Tile size for ESRGAN upscaler (default 128)

pub fn model<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to full model

pub fn diffusion_model<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to the standalone diffusion model

pub fn unconditional_diffusion_model<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to the standalone unconditional diffusion model, currently used by Ideogram4 CFG

pub fn llm<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the qwen2vl text encoder

pub fn llm_vision<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the qwen2vl vit

pub fn clip_l<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the clip-l text encoder

pub fn clip_g<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the clip-g text encoder

pub fn clip_vision<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the clip-vision encoder

pub fn t5xxl<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to the t5xxl text encoder

pub fn vae<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to vae

pub fn vae_format<VALUE: Into<VaeFormat>>(&mut self, value: VALUE) -> &mut Self

should match the VAE latent layout used by the PiD checkpoint. This is important when using standalone VAE files because the PiD diffusion checkpoint alone does not identify the VAE format.

pub fn taesd<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to taesd. Using Tiny AutoEncoder for fast decoding (low quality)

pub fn control_net<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to control net model

pub fn photo_maker<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to PHOTOMAKER model

pub fn pm_id_embed_path<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to PHOTOMAKER v2 id embed

pub fn weight_type<VALUE: Into<WeightType>>( &mut self, value: VALUE, ) -> &mut Self

Weight type. If not specified, the default is the type of the weight file

pub fn high_noise_diffusion_model<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to the standalone high noise diffusion model

pub fn vae_tiling<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Process vae in tiles to reduce memory usage (default: false)

pub fn vae_tile_size<VALUE: Into<(i32, i32)>>( &mut self, value: VALUE, ) -> &mut Self

Tile size for vae tiling (default: 32x32)

pub fn vae_relative_tile_size<VALUE: Into<(f32, f32)>>( &mut self, value: VALUE, ) -> &mut Self

Relative tile size for vae tiling, in fraction of image size if < 1, in number of tiles per dim if >=1 (overrides vae_tile_size)

pub fn vae_tile_overlap<VALUE: Into<f32>>(&mut self, value: VALUE) -> &mut Self

Tile overlap for vae tiling, in fraction of tile size (default: 0.5)

pub fn rng<VALUE: Into<RngFunction>>(&mut self, value: VALUE) -> &mut Self

RNG (default: CUDA)

pub fn sampler_rng_type<VALUE: Into<RngFunction>>( &mut self, value: VALUE, ) -> &mut Self

Sampler RNG. If RngFunction::RNG_TYPE_COUNT is used will default to rng value. (default: RngFunction::RNG_TYPE_COUNT)“,

pub fn scheduler<VALUE: Into<Scheduler>>(&mut self, value: VALUE) -> &mut Self

Denoiser sigma schedule (default: Scheduler::SCHEDULER_COUNT). Will default to Scheduler::EXPONENTIAL_SCHEDULER if a denoiser is already instantiated. Otherwise, Scheduler::DISCRETE_SCHEDULER is used.

pub fn sigmas<VALUE: Into<Vec<f32>>>(&mut self, value: VALUE) -> &mut Self

Custom sigma values for the sampler

pub fn prediction<VALUE: Into<Prediction>>(&mut self, value: VALUE) -> &mut Self

Prediction type override (default: PREDICTION_COUNT)

pub fn diffusion_flash_attention<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Use flash attention to reduce memory usage (model only). For most backends, it slows things down, but for cuda it generally speeds it up too. At the moment, it is only supported for some models and some backends (like cpu, cuda/rocm, metal).

pub fn flash_attention<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Use flash attention to reduce memory usage. For most backends, it slows things down, but for cuda it generally speeds it up too. At the moment, it is only supported for some models and some backends (like cpu, cuda/rocm, metal).

pub fn chroma_disable_dit_mask<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Disable dit mask for chroma

pub fn chroma_enable_t5_mask<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Enable t5 mask for chroma

pub fn chroma_t5_mask_pad<VALUE: Into<i32>>( &mut self, value: VALUE, ) -> &mut Self

t5 mask pad size of chroma

pub fn use_qwen_image_zero_cond_true<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Use qwen image zero cond true optimization

pub fn diffusion_conv_direct<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Use Conv2d direct in the diffusion model This might crash if it is not supported by the backend.

pub fn vae_conv_direct<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Use Conv2d direct in the vae model (should improve the performance) This might crash if it is not supported by the backend.

pub fn force_sdxl_vae_conv_scale<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Force use of conv scale on sdxl vae

pub fn flow_shift<VALUE: Into<f32>>(&mut self, value: VALUE) -> &mut Self

Shift value for Flow models like SD3.x or WAN (default: auto)

pub fn timestep_shift<VALUE: Into<i32>>(&mut self, value: VALUE) -> &mut Self

Shift timestep for NitroFusion models, default: 0, recommended N for NitroSD-Realism around 250 and 500 for NitroSD-Vibrant

pub fn taesd_preview_only<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Prevents usage of taesd for decoding the final image

pub fn lora_apply_mode<VALUE: Into<LoraModeType>>( &mut self, value: VALUE, ) -> &mut Self

In auto mode, if the model weights contain any quantized parameters, the at_runtime mode will be used; otherwise, immediately will be used.The immediate mode may have precision and compatibility issues with quantized parameters, but it usually offers faster inference speed and, in some cases, lower memory usage. The at_runtime mode, on the other hand, is exactly the opposite

pub fn circular<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Enable circular padding for convolutions

pub fn circular_x<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Enable circular RoPE wrapping on x-axis (width) only

pub fn circular_y<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Enable circular RoPE wrapping on y-axis (height) only

pub fn extra_sample_params<VALUE: Into<CLibString>>( &mut self, value: VALUE, ) -> &mut Self

Extra parameters for sampling, currently used for SDXL sample params, in json string format

pub fn embeddings_connectors<VALUE: Into<CLibPath>>( &mut self, value: VALUE, ) -> &mut Self

Path to LTXAV embeddings connectors

pub fn audio_vae<VALUE: Into<CLibPath>>(&mut self, value: VALUE) -> &mut Self

Path to standalone LTX audio vae model

pub fn vae_temporal_tiling<VALUE: Into<bool>>( &mut self, value: VALUE, ) -> &mut Self

Enable temporal tiling for LTX video VAE decode

pub fn stream_layers<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Enable residency+prefetch streaming on top of ModelConfig::max_vram (no effect without ModelConfig::max_vram; defaults to false)

pub fn build(&self) -> Result<ModelConfig, ConfigBuilderError>

Builds a new ModelConfig.

Errors

If a required field has not been initialized.

impl ModelConfigBuilder

pub fn embeddings(&mut self, embeddings_dir: &Path) -> &mut Self

pub fn lora_models( &mut self, lora_model_dir: &Path, specs: Vec<LoraSpec>, ) -> &mut Self

pub fn n_threads(&mut self, value: i32) -> &mut Self

pub fn hires_params( &mut self, upscaler: Upscaler, params: HiresParams, custom_model: Option<&Path>, ) -> &mut Self

pub fn backend( &mut self, backend_map: HashMap<Module, BackendDevice>, ) -> &mut Self

pub fn params_backend( &mut self, backend_map: HashMap<Module, BackendDevice>, ) -> &mut Self

pub fn extra_tiling_args( &mut self, extra_tiling_args_map: HashMap<String, String>, ) -> &mut Self

Trait Implementations

impl Clone for ModelConfigBuilder

fn clone(&self) -> ModelConfigBuilder

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Default for ModelConfigBuilder

fn default() -> Self

Returns the “default value” for a type.

impl From<&ModelConfig> for ModelConfigBuilder

fn from(value: &ModelConfig) -> Self

Converts to this type from the input type.