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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

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Brandon Rising 2024-08-19 14:41:28 -04:00 committed by Brandon
parent 4bd7fda694
commit a63f842a13
9 changed files with 170 additions and 66 deletions
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16
invokeai/app/invocations/flux_text_encoder.py
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@ -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.
# 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}")
max_seq_len = self.max_seq_len
# 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_text_encoder_info = context.models.load(self.t5Encoder.text_encoder)
t5_tokenizer_info = context.models.load(self.t5_encoder.tokenizer)
t5_text_encoder_info = context.models.load(self.t5_encoder.text_encoder)
with (
clip_text_encoder_info as clip_text_encoder,

3
invokeai/app/invocations/flux_text_to_image.py
View File

@ -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],

17
invokeai/app/invocations/model.py
View File

@ -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:

3
invokeai/backend/model_manager/load/model_loaders/flux.py
View File

@ -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():

9
invokeai/backend/model_manager/probe.py
View File

@ -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

16
invokeai/configs/flux/flux1-dev.yaml
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@ -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

17
invokeai/configs/flux/flux1-schnell.yaml
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@ -1,7 +1,6 @@
repo_id: "black-forest-labs/FLUX.1-schnell"
repo_ae: "ae.safetensors"
t5_encoder: "google/t5-v1_1-xxl"
max_length: 512
max_seq_len: 256
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

16
invokeai/configs/flux/flux1-vae.yaml Normal file
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@ -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

139
invokeai/frontend/web/src/services/api/schema.ts
View File

@ -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 */