Select dev/schnell based on state dict, use correct max seq len based on dev/schnell, and shift in inference, separate vae flux params into separate config

invokeai/app/invocations/flux_text_encoder.py

@@ -1,4 +1,5 @@
 import torch
+from typing import Literal
 from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
@@ -23,11 +24,12 @@ class FluxTextEncoderInvocation(BaseInvocation):
         description=FieldDescriptions.clip,
         input=Input.Connection,
     )
-    t5Encoder: T5EncoderField = InputField(
+    t5_encoder: T5EncoderField = InputField(
         title="T5Encoder",
         description=FieldDescriptions.t5Encoder,
         input=Input.Connection,
     )
+    max_seq_len: Literal[256, 512] = InputField(description="Max sequence length for the desired flux model")
     positive_prompt: str = InputField(description="Positive prompt for text-to-image generation.")
 
     # TODO(ryand): Should we create a new return type for this invocation? This ConditioningOutput is clearly not
@@ -43,21 +45,15 @@ class FluxTextEncoderInvocation(BaseInvocation):
         return ConditioningOutput.build(conditioning_name)
 
     def _encode_prompt(self, context: InvocationContext) -> tuple[torch.Tensor, torch.Tensor]:
-        # TODO: Determine the T5 max sequence length based on the model.
+        max_seq_len = self.max_seq_len
-        # if self.model == "flux-schnell":
-        max_seq_len = 256
-        # # elif self.model == "flux-dev":
-        # #     max_seq_len = 512
-        # else:
-        #     raise ValueError(f"Unknown model: {self.model}")
 
         # Load CLIP.
         clip_tokenizer_info = context.models.load(self.clip.tokenizer)
         clip_text_encoder_info = context.models.load(self.clip.text_encoder)
 
         # Load T5.
-        t5_tokenizer_info = context.models.load(self.t5Encoder.tokenizer)
+        t5_tokenizer_info = context.models.load(self.t5_encoder.tokenizer)
-        t5_text_encoder_info = context.models.load(self.t5Encoder.text_encoder)
+        t5_text_encoder_info = context.models.load(self.t5_encoder.text_encoder)
 
         with (
             clip_text_encoder_info as clip_text_encoder,

invokeai/app/invocations/flux_text_to_image.py

@@ -19,6 +19,7 @@ from invokeai.backend.flux.modules.autoencoder import AutoEncoder
 from invokeai.backend.flux.sampling import denoise, get_noise, get_schedule, unpack
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import FLUXConditioningInfo
 from invokeai.backend.util.devices import TorchDevice
+from invokeai.backend.model_manager.config import CheckpointConfigBase
 
 
 @invocation(
@@ -89,7 +90,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         img, img_ids = self._prepare_latent_img_patches(x)
 
         # HACK(ryand): Find a better way to determine if this is a schnell model or not.
-        is_schnell = "schnell" in transformer_info.config.path if transformer_info.config else ""
+        is_schnell = "schnell" in transformer_info.config.config_path if transformer_info.config and isinstance(transformer_info.config, CheckpointConfigBase) else ""
         timesteps = get_schedule(
             num_steps=self.num_steps,
             image_seq_len=img.shape[1],

invokeai/app/invocations/model.py

@@ -1,4 +1,5 @@
 import copy
+import yaml
 from time import sleep
 from typing import Dict, List, Literal, Optional
 
@@ -16,6 +17,7 @@ from invokeai.app.services.model_records import ModelRecordChanges
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.shared.models import FreeUConfig
 from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.config import CheckpointConfigBase
 
 
 class ModelIdentifierField(BaseModel):
@@ -154,8 +156,9 @@ class FluxModelLoaderOutput(BaseInvocationOutput):
 
     transformer: TransformerField = OutputField(description=FieldDescriptions.transformer, title="Transformer")
     clip: CLIPField = OutputField(description=FieldDescriptions.clip, title="CLIP")
-    t5Encoder: T5EncoderField = OutputField(description=FieldDescriptions.t5Encoder, title="T5 Encoder")
+    t5_encoder: T5EncoderField = OutputField(description=FieldDescriptions.t5Encoder, title="T5 Encoder")
     vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE")
+    max_seq_len: Literal[256, 512] = OutputField(description=FieldDescriptions.vae, title="Max Seq Length")
 
 
 @invocation("flux_model_loader", title="Flux Main Model", tags=["model", "flux"], category="model", version="1.0.3")
@@ -189,12 +192,22 @@ class FluxModelLoaderInvocation(BaseInvocation):
             ModelType.VAE,
             BaseModelType.Flux,
         )
+        transformer_config = context.models.get_config(transformer)
+        assert isinstance(transformer_config, CheckpointConfigBase)
+        legacy_config_path = context.config.get().legacy_conf_path / transformer_config.config_path
+        config_path = legacy_config_path.as_posix()
+        with open(config_path, "r") as stream:
+            try:
+                flux_conf = yaml.safe_load(stream)
+            except:
+                raise
 
         return FluxModelLoaderOutput(
             transformer=TransformerField(transformer=transformer),
             clip=CLIPField(tokenizer=tokenizer, text_encoder=clip_encoder, loras=[], skipped_layers=0),
-            t5Encoder=T5EncoderField(tokenizer=tokenizer2, text_encoder=t5_encoder),
+            t5_encoder=T5EncoderField(tokenizer=tokenizer2, text_encoder=t5_encoder),
             vae=VAEField(vae=vae),
+            max_seq_len=flux_conf['max_seq_len']
         )
 
     def _get_model(self, context: InvocationContext, submodel: SubModelType) -> ModelIdentifierField:

invokeai/backend/model_manager/load/model_loaders/flux.py

@@ -32,7 +32,6 @@ from invokeai.backend.model_manager.config import (
 )
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
 from invokeai.backend.model_manager.load.model_loaders.generic_diffusers import GenericDiffusersLoader
-from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4
 
@@ -60,7 +59,7 @@ class FluxVAELoader(GenericDiffusersLoader):
                     raise
 
             dataclass_fields = {f.name for f in fields(AutoEncoderParams)}
-            filtered_data = {k: v for k, v in flux_conf["params"]["ae_params"].items() if k in dataclass_fields}
+            filtered_data = {k: v for k, v in flux_conf["params"].items() if k in dataclass_fields}
             params = AutoEncoderParams(**filtered_data)
 
             with SilenceWarnings():

invokeai/backend/model_manager/probe.py

@@ -324,7 +324,12 @@ class ModelProbe(object):
         if model_type is ModelType.Main:
             if base_type == BaseModelType.Flux:
                 # TODO: Decide between dev/schnell
-                config_file = "flux/flux1-schnell.yaml"
+                checkpoint = ModelProbe._scan_and_load_checkpoint(model_path)
+                state_dict = checkpoint.get("state_dict") or checkpoint
+                if 'guidance_in.out_layer.weight' in state_dict:
+                    config_file = "flux/flux1-dev.yaml"
+                else:
+                    config_file = "flux/flux1-schnell.yaml"
             else:
                 config_file = LEGACY_CONFIGS[base_type][variant_type]
                 if isinstance(config_file, dict):  # need another tier for sd-2.x models
@@ -338,7 +343,7 @@ class ModelProbe(object):
             )
         elif model_type is ModelType.VAE:
             config_file = (
-                "flux/flux1-schnell.yaml"
+                "flux/flux1-vae.yaml"
                 if base_type is BaseModelType.Flux
                 else "stable-diffusion/v1-inference.yaml"
                 if base_type is BaseModelType.StableDiffusion1

invokeai/configs/flux/flux1-dev.yaml

@@ -1,6 +1,6 @@
 repo_id: "black-forest-labs/FLUX.1-dev"
 repo_ae: "ae.safetensors"
-max_length: 512
+max_seq_len: 512
 params:
   in_channels: 64
   vec_in_dim: 768
@@ -17,17 +17,3 @@ params:
   theta: 10_000
   qkv_bias: True
   guidance_embed: True
-  ae_params:
-    resolution: 256
-    in_channels: 3
-    ch: 128
-    out_ch: 3
-    ch_mult:
-    - 1
-    - 2
-    - 4
-    - 4
-    num_res_blocks: 2
-    z_channels: 16
-    scale_factor: 0.3611
-    shift_factor: 0.1159

invokeai/configs/flux/flux1-schnell.yaml

@@ -1,7 +1,6 @@
 repo_id: "black-forest-labs/FLUX.1-schnell"
 repo_ae: "ae.safetensors"
-t5_encoder: "google/t5-v1_1-xxl"
+max_seq_len: 256
-max_length: 512
 params:
   in_channels: 64
   vec_in_dim: 768
@@ -18,17 +17,3 @@ params:
   theta: 10_000
   qkv_bias: True
   guidance_embed: False
-  ae_params:
-    resolution: 256
-    in_channels: 3
-    ch: 128
-    out_ch: 3
-    ch_mult:
-    - 1
-    - 2
-    - 4
-    - 4
-    num_res_blocks: 2
-    z_channels: 16
-    scale_factor: 0.3611
-    shift_factor: 0.1159

invokeai/configs/flux/flux1-vae.yaml

@@ -0,0 +1,16 @@
+repo_id: "black-forest-labs/FLUX.1-schnell"
+repo_path: "ae.safetensors"
+params:
+  resolution: 256
+  in_channels: 3
+  ch: 128
+  out_ch: 3
+  ch_mult:
+  - 1
+  - 2
+  - 4
+  - 4
+  num_res_blocks: 2
+  z_channels: 16
+  scale_factor: 0.3611
+  shift_factor: 0.1159

invokeai/frontend/web/src/services/api/schema.ts

@@ -3735,11 +3735,11 @@ export type components = {
             cover_image?: string | null;
             /**
              * Format
+             * @description Format of the provided checkpoint model
              * @default checkpoint
-             * @constant
              * @enum {string}
              */
-            format: "checkpoint";
+            format: "checkpoint" | "bnb_quantized_nf4b";
             /**
              * Config Path
              * @description path to the checkpoint model config file
@@ -5750,7 +5750,7 @@ export type components = {
              * @default null
              * @enum {string}
              */
-            t5_encoder?: "base" | "16b_quantized" | "8b_quantized";
+            t5_encoder?: "base" | "8b_quantized";
             /**
              * type
              * @default flux_model_loader
@@ -5778,12 +5778,18 @@ export type components = {
              * T5 Encoder
              * @description T5 tokenizer and text encoder
              */
-            t5Encoder: components["schemas"]["T5EncoderField"];
+            t5_encoder: components["schemas"]["T5EncoderField"];
             /**
              * VAE
              * @description VAE
              */
             vae: components["schemas"]["VAEField"];
+            /**
+             * Max Seq Length
+             * @description VAE
+             * @enum {integer}
+             */
+            max_seq_len: 256 | 512;
             /**
              * type
              * @default flux_model_loader_output
@@ -5822,7 +5828,14 @@ export type components = {
              * @description T5 tokenizer and text encoder
              * @default null
              */
-            t5Encoder?: components["schemas"]["T5EncoderField"];
+            t5_encoder?: components["schemas"]["T5EncoderField"];
+            /**
+             * Max Seq Len
+             * @description Max sequence length for the desired flux model
+             * @default null
+             * @enum {integer}
+             */
+            max_seq_len?: 256 | 512;
             /**
              * Positive Prompt
              * @description Positive prompt for text-to-image generation.
@@ -9694,6 +9707,96 @@ export type components = {
          * @enum {integer}
          */
         LogLevel: 0 | 10 | 20 | 30 | 40 | 50;
+        /**
+         * MainBnbQuantized4bCheckpointConfig
+         * @description Model config for main checkpoint models.
+         */
+        MainBnbQuantized4bCheckpointConfig: {
+            /**
+             * Key
+             * @description A unique key for this model.
+             */
+            key: string;
+            /**
+             * Hash
+             * @description The hash of the model file(s).
+             */
+            hash: string;
+            /**
+             * Path
+             * @description Path to the model on the filesystem. Relative paths are relative to the Invoke root directory.
+             */
+            path: string;
+            /**
+             * Name
+             * @description Name of the model.
+             */
+            name: string;
+            /** @description The base model. */
+            base: components["schemas"]["BaseModelType"];
+            /**
+             * Description
+             * @description Model description
+             */
+            description?: string | null;
+            /**
+             * Source
+             * @description The original source of the model (path, URL or repo_id).
+             */
+            source: string;
+            /** @description The type of source */
+            source_type: components["schemas"]["ModelSourceType"];
+            /**
+             * Source Api Response
+             * @description The original API response from the source, as stringified JSON.
+             */
+            source_api_response?: string | null;
+            /**
+             * Cover Image
+             * @description Url for image to preview model
+             */
+            cover_image?: string | null;
+            /**
+             * Type
+             * @default main
+             * @constant
+             * @enum {string}
+             */
+            type: "main";
+            /**
+             * Trigger Phrases
+             * @description Set of trigger phrases for this model
+             */
+            trigger_phrases?: string[] | null;
+            /** @description Default settings for this model */
+            default_settings?: components["schemas"]["MainModelDefaultSettings"] | null;
+            /** @default normal */
+            variant?: components["schemas"]["ModelVariantType"];
+            /**
+             * Format
+             * @description Format of the provided checkpoint model
+             * @default checkpoint
+             * @enum {string}
+             */
+            format: "checkpoint" | "bnb_quantized_nf4b";
+            /**
+             * Config Path
+             * @description path to the checkpoint model config file
+             */
+            config_path: string;
+            /**
+             * Converted At
+             * @description When this model was last converted to diffusers
+             */
+            converted_at?: number | null;
+            /** @default epsilon */
+            prediction_type?: components["schemas"]["SchedulerPredictionType"];
+            /**
+             * Upcast Attention
+             * @default false
+             */
+            upcast_attention?: boolean;
+        };
         /**
          * MainCheckpointConfig
          * @description Model config for main checkpoint models.
@@ -9761,11 +9864,11 @@ export type components = {
             variant?: components["schemas"]["ModelVariantType"];
             /**
              * Format
+             * @description Format of the provided checkpoint model
              * @default checkpoint
-             * @constant
              * @enum {string}
              */
-            format: "checkpoint";
+            format: "checkpoint" | "bnb_quantized_nf4b";
             /**
              * Config Path
              * @description path to the checkpoint model config file
@@ -10670,7 +10773,7 @@ export type components = {
          * @description Storage format of model.
          * @enum {string}
          */
-        ModelFormat: "diffusers" | "checkpoint" | "lycoris" | "onnx" | "olive" | "embedding_file" | "embedding_folder" | "invokeai" | "t5_encoder" | "t5_encoder_8b" | "t5_encoder_4b";
+        ModelFormat: "diffusers" | "checkpoint" | "lycoris" | "onnx" | "olive" | "embedding_file" | "embedding_folder" | "invokeai" | "t5_encoder" | "t5_encoder_8b" | "t5_encoder_4b" | "bnb_quantized_nf4b";
         /** ModelIdentifierField */
         ModelIdentifierField: {
             /**
@@ -10970,7 +11073,7 @@ export type components = {
              * Config Out
              * @description After successful installation, this will hold the configuration object.
              */
-            config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"]) | null;
+            config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"]) | null;
             /**
              * Inplace
              * @description Leave model in its current location; otherwise install under models directory
@@ -11056,7 +11159,7 @@ export type components = {
              * Config
              * @description The model's config
              */
-            config: components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+            config: components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
             /**
              * @description The submodel type, if any
              * @default null
@@ -11077,7 +11180,7 @@ export type components = {
              * Config
              * @description The model's config
              */
-            config: components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+            config: components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
             /**
              * @description The submodel type, if any
              * @default null
@@ -11218,7 +11321,7 @@ export type components = {
          */
         ModelsList: {
             /** Models */
-            models: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"])[];
+            models: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"])[];
         };
         /**
          * Multiply Integers
@@ -15087,11 +15190,11 @@ export type components = {
             cover_image?: string | null;
             /**
              * Format
+             * @description Format of the provided checkpoint model
              * @default checkpoint
-             * @constant
              * @enum {string}
              */
-            format: "checkpoint";
+            format: "checkpoint" | "bnb_quantized_nf4b";
             /**
              * Config Path
              * @description path to the checkpoint model config file
@@ -15619,7 +15722,7 @@ export interface operations {
                     [name: string]: unknown;
                 };
                 content: {
-                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
                 };
             };
             /** @description Validation Error */
@@ -15651,7 +15754,7 @@ export interface operations {
                     [name: string]: unknown;
                 };
                 content: {
-                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
                 };
             };
             /** @description Bad request */
@@ -15748,7 +15851,7 @@ export interface operations {
                     [name: string]: unknown;
                 };
                 content: {
-                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
                 };
             };
             /** @description Bad request */
@@ -16248,7 +16351,7 @@ export interface operations {
                     [name: string]: unknown;
                 };
                 content: {
-                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
+                    "application/json": components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"] | components["schemas"]["MainBnbQuantized4bCheckpointConfig"] | components["schemas"]["VAEDiffusersConfig"] | components["schemas"]["VAECheckpointConfig"] | components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"] | components["schemas"]["LoRALyCORISConfig"] | components["schemas"]["LoRADiffusersConfig"] | components["schemas"]["T5EncoderConfig"] | components["schemas"]["TextualInversionFileConfig"] | components["schemas"]["TextualInversionFolderConfig"] | components["schemas"]["IPAdapterInvokeAIConfig"] | components["schemas"]["IPAdapterCheckpointConfig"] | components["schemas"]["T2IAdapterConfig"] | components["schemas"]["SpandrelImageToImageConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["CLIPEmbedDiffusersConfig"];
                 };
             };
             /** @description Bad request */