Struct ModelConfig 

pub struct ModelConfig {

    pub transformer: Option<String>,
    pub transformer_shards: Option<Vec<String>>,
    pub vae: Option<String>,
    pub spatial_upscaler: Option<String>,
    pub temporal_upscaler: Option<String>,
    pub distilled_lora: Option<String>,
    pub t5_encoder: Option<String>,
    pub clip_encoder: Option<String>,
    pub t5_tokenizer: Option<String>,
    pub clip_tokenizer: Option<String>,
    pub clip_encoder_2: Option<String>,
    pub clip_tokenizer_2: Option<String>,
    pub text_encoder_files: Option<Vec<String>>,
    pub text_tokenizer: Option<String>,
    pub decoder: Option<String>,
    pub default_steps: Option<u32>,
    pub default_guidance: Option<f64>,
    pub default_width: Option<u32>,
    pub default_height: Option<u32>,
    pub is_schnell: Option<bool>,
    pub is_turbo: Option<bool>,
    pub scheduler: Option<Scheduler>,
    pub negative_prompt: Option<String>,
    pub lora: Option<String>,
    pub lora_scale: Option<f64>,
    pub default_frames: Option<u32>,
    pub default_fps: Option<u32>,
    pub description: Option<String>,
    pub family: Option<String>,
}

Per-model file path + default settings configuration.

Fields

transformer: Option<String>

transformer_shards: Option<Vec<String>>

Multi-shard transformer paths (Z-Image BF16); empty means use single transformer

vae: Option<String>

spatial_upscaler: Option<String>

LTX latent upsampler / spatial upscaler weights.

temporal_upscaler: Option<String>

Optional temporal upscaler weights for LTX-2/LTX-2.3.

distilled_lora: Option<String>

Optional distilled LoRA bundled with a model manifest.

t5_encoder: Option<String>

clip_encoder: Option<String>

t5_tokenizer: Option<String>

clip_tokenizer: Option<String>

clip_encoder_2: Option<String>

CLIP-G / OpenCLIP encoder path (SDXL only)

clip_tokenizer_2: Option<String>

CLIP-G / OpenCLIP tokenizer path (SDXL only)

text_encoder_files: Option<Vec<String>>

Generic text encoder shard paths (Qwen3 for Z-Image)

text_tokenizer: Option<String>

Generic text encoder tokenizer path (Qwen3 for Z-Image)

decoder: Option<String>

Stage B decoder weights path (Wuerstchen only)

default_steps: Option<u32>

Default inference steps (e.g. 4 for schnell, 25 for dev)

default_guidance: Option<f64>

Default guidance scale (0.0 for schnell, 3.5 for dev finetuned)

default_width: Option<u32>

Default output width

default_height: Option<u32>

Default output height

is_schnell: Option<bool>

Whether this model uses the schnell (distilled) timestep schedule. If None, auto-detected from the transformer filename.

is_turbo: Option<bool>

Whether this model uses a turbo (few-step distilled) schedule. If None, auto-detected from the model name.

scheduler: Option<Scheduler>

Scheduler algorithm for UNet-based models (SD1.5, SDXL). Ignored by flow-matching models.

negative_prompt: Option<String>

Per-model default negative prompt for CFG-based models.

lora: Option<String>

Default LoRA adapter path for this model.

lora_scale: Option<f64>

Default LoRA scale for this model (0.0-2.0).

default_frames: Option<u32>

Default number of video frames for video models (e.g. 25 for ltx-video).

default_fps: Option<u32>

Default video FPS for video models (e.g. 24 for ltx-video).

description: Option<String>

family: Option<String>

Implementations

impl ModelConfig

pub fn all_file_paths(&self) -> Vec<String>

Collect all file path strings from this model config into a flat list. Used for reference counting when determining which files are shared.

pub fn disk_usage(&self) -> (u64, f64)

Total disk usage of all model files: (bytes, gigabytes).

Sums the file sizes of all paths referenced by this config entry. Missing files are silently skipped.

pub fn effective_steps(&self, global_cfg: &Config) -> u32

Effective steps: model default → global fallback → hardcoded default.

pub fn effective_guidance(&self) -> f64

Effective guidance.

pub fn effective_width(&self, global_cfg: &Config) -> u32

Effective width.

pub fn effective_height(&self, global_cfg: &Config) -> u32

Effective height.

pub fn effective_negative_prompt(&self, global_cfg: &Config) -> Option<String>

Effective negative prompt: per-model override → global default → None.

pub fn effective_lora(&self) -> Option<(String, f64)>

Effective LoRA config: per-model default path and scale, or None.

pub fn effective_frames(&self) -> Option<u32>

Effective video frames: per-model default, or None for image-only models.

pub fn effective_fps(&self) -> Option<u32>

Effective video FPS: per-model default, or None for image-only models.

Trait Implementations

impl Clone for ModelConfig

fn clone(&self) -> ModelConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ModelConfig

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for ModelConfig

fn default() -> ModelConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for ModelConfig

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for ModelConfig

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.