mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
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
This commit is contained in:
Brandon Rising
Brandon
parent
4bd7fda694
commit
a63f842a13
@ -1,4 +1,5 @@
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import torch
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from typing import Literal
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from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer
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from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
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@ -23,11 +24,12 @@ class FluxTextEncoderInvocation(BaseInvocation):
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description=FieldDescriptions.clip,
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input=Input.Connection,
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)
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t5Encoder: T5EncoderField = InputField(
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t5_encoder: T5EncoderField = InputField(
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title="T5Encoder",
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description=FieldDescriptions.t5Encoder,
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input=Input.Connection,
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)
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max_seq_len: Literal[256, 512] = InputField(description="Max sequence length for the desired flux model")
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positive_prompt: str = InputField(description="Positive prompt for text-to-image generation.")
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# TODO(ryand): Should we create a new return type for this invocation? This ConditioningOutput is clearly not
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@ -43,21 +45,15 @@ class FluxTextEncoderInvocation(BaseInvocation):
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return ConditioningOutput.build(conditioning_name)
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def _encode_prompt(self, context: InvocationContext) -> tuple[torch.Tensor, torch.Tensor]:
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# TODO: Determine the T5 max sequence length based on the model.
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# if self.model == "flux-schnell":
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max_seq_len = 256
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# # elif self.model == "flux-dev":
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# # max_seq_len = 512
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# else:
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# raise ValueError(f"Unknown model: {self.model}")
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max_seq_len = self.max_seq_len
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# Load CLIP.
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clip_tokenizer_info = context.models.load(self.clip.tokenizer)
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clip_text_encoder_info = context.models.load(self.clip.text_encoder)
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# Load T5.
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t5_tokenizer_info = context.models.load(self.t5Encoder.tokenizer)
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t5_text_encoder_info = context.models.load(self.t5Encoder.text_encoder)
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t5_tokenizer_info = context.models.load(self.t5_encoder.tokenizer)
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t5_text_encoder_info = context.models.load(self.t5_encoder.text_encoder)
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with (
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clip_text_encoder_info as clip_text_encoder,
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@ -19,6 +19,7 @@ from invokeai.backend.flux.modules.autoencoder import AutoEncoder
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from invokeai.backend.flux.sampling import denoise, get_noise, get_schedule, unpack
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import FLUXConditioningInfo
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from invokeai.backend.util.devices import TorchDevice
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from invokeai.backend.model_manager.config import CheckpointConfigBase
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@invocation(
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@ -89,7 +90,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
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img, img_ids = self._prepare_latent_img_patches(x)
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# HACK(ryand): Find a better way to determine if this is a schnell model or not.
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is_schnell = "schnell" in transformer_info.config.path if transformer_info.config else ""
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is_schnell = "schnell" in transformer_info.config.config_path if transformer_info.config and isinstance(transformer_info.config, CheckpointConfigBase) else ""
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timesteps = get_schedule(
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num_steps=self.num_steps,
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image_seq_len=img.shape[1],
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@ -1,4 +1,5 @@
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import copy
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import yaml
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from time import sleep
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from typing import Dict, List, Literal, Optional
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@ -16,6 +17,7 @@ from invokeai.app.services.model_records import ModelRecordChanges
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.app.shared.models import FreeUConfig
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from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
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from invokeai.backend.model_manager.config import CheckpointConfigBase
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class ModelIdentifierField(BaseModel):
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@ -154,8 +156,9 @@ class FluxModelLoaderOutput(BaseInvocationOutput):
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transformer: TransformerField = OutputField(description=FieldDescriptions.transformer, title="Transformer")
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clip: CLIPField = OutputField(description=FieldDescriptions.clip, title="CLIP")
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t5Encoder: T5EncoderField = OutputField(description=FieldDescriptions.t5Encoder, title="T5 Encoder")
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t5_encoder: T5EncoderField = OutputField(description=FieldDescriptions.t5Encoder, title="T5 Encoder")
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vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE")
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max_seq_len: Literal[256, 512] = OutputField(description=FieldDescriptions.vae, title="Max Seq Length")
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@invocation("flux_model_loader", title="Flux Main Model", tags=["model", "flux"], category="model", version="1.0.3")
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@ -189,12 +192,22 @@ class FluxModelLoaderInvocation(BaseInvocation):
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ModelType.VAE,
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BaseModelType.Flux,
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)
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transformer_config = context.models.get_config(transformer)
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assert isinstance(transformer_config, CheckpointConfigBase)
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legacy_config_path = context.config.get().legacy_conf_path / transformer_config.config_path
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config_path = legacy_config_path.as_posix()
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with open(config_path, "r") as stream:
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try:
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flux_conf = yaml.safe_load(stream)
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except:
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raise
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return FluxModelLoaderOutput(
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transformer=TransformerField(transformer=transformer),
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clip=CLIPField(tokenizer=tokenizer, text_encoder=clip_encoder, loras=[], skipped_layers=0),
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t5Encoder=T5EncoderField(tokenizer=tokenizer2, text_encoder=t5_encoder),
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t5_encoder=T5EncoderField(tokenizer=tokenizer2, text_encoder=t5_encoder),
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vae=VAEField(vae=vae),
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max_seq_len=flux_conf['max_seq_len']
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)
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def _get_model(self, context: InvocationContext, submodel: SubModelType) -> ModelIdentifierField:
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@ -32,7 +32,6 @@ from invokeai.backend.model_manager.config import (
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)
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from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
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from invokeai.backend.model_manager.load.model_loaders.generic_diffusers import GenericDiffusersLoader
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from invokeai.backend.util.devices import TorchDevice
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from invokeai.backend.util.silence_warnings import SilenceWarnings
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from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4
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@ -60,7 +59,7 @@ class FluxVAELoader(GenericDiffusersLoader):
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raise
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dataclass_fields = {f.name for f in fields(AutoEncoderParams)}
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filtered_data = {k: v for k, v in flux_conf["params"]["ae_params"].items() if k in dataclass_fields}
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filtered_data = {k: v for k, v in flux_conf["params"].items() if k in dataclass_fields}
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params = AutoEncoderParams(**filtered_data)
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with SilenceWarnings():
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@ -324,7 +324,12 @@ class ModelProbe(object):
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if model_type is ModelType.Main:
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if base_type == BaseModelType.Flux:
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# TODO: Decide between dev/schnell
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config_file = "flux/flux1-schnell.yaml"
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checkpoint = ModelProbe._scan_and_load_checkpoint(model_path)
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state_dict = checkpoint.get("state_dict") or checkpoint
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if 'guidance_in.out_layer.weight' in state_dict:
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config_file = "flux/flux1-dev.yaml"
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else:
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config_file = "flux/flux1-schnell.yaml"
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else:
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config_file = LEGACY_CONFIGS[base_type][variant_type]
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if isinstance(config_file, dict): # need another tier for sd-2.x models
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@ -338,7 +343,7 @@ class ModelProbe(object):
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)
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elif model_type is ModelType.VAE:
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config_file = (
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"flux/flux1-schnell.yaml"
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"flux/flux1-vae.yaml"
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if base_type is BaseModelType.Flux
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else "stable-diffusion/v1-inference.yaml"
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if base_type is BaseModelType.StableDiffusion1
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@ -1,6 +1,6 @@
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repo_id: "black-forest-labs/FLUX.1-dev"
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repo_ae: "ae.safetensors"
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max_length: 512
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max_seq_len: 512
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params:
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in_channels: 64
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vec_in_dim: 768
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@ -17,17 +17,3 @@ params:
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theta: 10_000
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qkv_bias: True
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guidance_embed: True
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ae_params:
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resolution: 256
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in_channels: 3
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ch: 128
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out_ch: 3
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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z_channels: 16
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scale_factor: 0.3611
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shift_factor: 0.1159
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@ -1,7 +1,6 @@
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repo_id: "black-forest-labs/FLUX.1-schnell"
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repo_ae: "ae.safetensors"
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t5_encoder: "google/t5-v1_1-xxl"
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max_length: 512
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max_seq_len: 256
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params:
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in_channels: 64
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vec_in_dim: 768
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@ -18,17 +17,3 @@ params:
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theta: 10_000
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qkv_bias: True
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guidance_embed: False
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ae_params:
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resolution: 256
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in_channels: 3
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ch: 128
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out_ch: 3
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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z_channels: 16
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scale_factor: 0.3611
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shift_factor: 0.1159
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16
invokeai/configs/flux/flux1-vae.yaml
Normal file
16
invokeai/configs/flux/flux1-vae.yaml
Normal file
@ -0,0 +1,16 @@
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repo_id: "black-forest-labs/FLUX.1-schnell"
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repo_path: "ae.safetensors"
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params:
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resolution: 256
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in_channels: 3
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ch: 128
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out_ch: 3
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ch_mult:
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- 1
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- 2
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- 4
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- 4
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num_res_blocks: 2
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z_channels: 16
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scale_factor: 0.3611
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shift_factor: 0.1159
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@ -3735,11 +3735,11 @@ export type components = {
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cover_image?: string | null;
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/**
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* Format
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* @description Format of the provided checkpoint model
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* @default checkpoint
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* @constant
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* @enum {string}
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*/
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format: "checkpoint";
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format: "checkpoint" | "bnb_quantized_nf4b";
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/**
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* Config Path
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* @description path to the checkpoint model config file
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@ -5750,7 +5750,7 @@ export type components = {
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* @default null
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* @enum {string}
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*/
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t5_encoder?: "base" | "16b_quantized" | "8b_quantized";
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t5_encoder?: "base" | "8b_quantized";
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/**
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* type
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* @default flux_model_loader
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@ -5778,12 +5778,18 @@ export type components = {
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* T5 Encoder
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* @description T5 tokenizer and text encoder
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*/
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t5Encoder: components["schemas"]["T5EncoderField"];
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t5_encoder: components["schemas"]["T5EncoderField"];
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/**
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* VAE
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* @description VAE
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*/
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vae: components["schemas"]["VAEField"];
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/**
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* Max Seq Length
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* @description VAE
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* @enum {integer}
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*/
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max_seq_len: 256 | 512;
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/**
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* type
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* @default flux_model_loader_output
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@ -5822,7 +5828,14 @@ export type components = {
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* @description T5 tokenizer and text encoder
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* @default null
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*/
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t5Encoder?: components["schemas"]["T5EncoderField"];
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t5_encoder?: components["schemas"]["T5EncoderField"];
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/**
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* Max Seq Len
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* @description Max sequence length for the desired flux model
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* @default null
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* @enum {integer}
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*/
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max_seq_len?: 256 | 512;
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/**
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* Positive Prompt
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* @description Positive prompt for text-to-image generation.
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@ -9694,6 +9707,96 @@ export type components = {
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* @enum {integer}
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*/
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LogLevel: 0 | 10 | 20 | 30 | 40 | 50;
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/**
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* MainBnbQuantized4bCheckpointConfig
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* @description Model config for main checkpoint models.
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*/
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MainBnbQuantized4bCheckpointConfig: {
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/**
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* Key
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* @description A unique key for this model.
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*/
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key: string;
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/**
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* Hash
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* @description The hash of the model file(s).
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*/
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hash: string;
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/**
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* Path
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* @description Path to the model on the filesystem. Relative paths are relative to the Invoke root directory.
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*/
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path: string;
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/**
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* Name
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* @description Name of the model.
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*/
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name: string;
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/** @description The base model. */
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base: components["schemas"]["BaseModelType"];
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/**
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* Description
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* @description Model description
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*/
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description?: string | null;
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/**
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* Source
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* @description The original source of the model (path, URL or repo_id).
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*/
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source: string;
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/** @description The type of source */
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source_type: components["schemas"]["ModelSourceType"];
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/**
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* Source Api Response
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* @description The original API response from the source, as stringified JSON.
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*/
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source_api_response?: string | null;
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/**
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* Cover Image
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* @description Url for image to preview model
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*/
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cover_image?: string | null;
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/**
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* Type
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* @default main
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* @constant
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* @enum {string}
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*/
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type: "main";
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/**
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* Trigger Phrases
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* @description Set of trigger phrases for this model
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*/
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trigger_phrases?: string[] | null;
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/** @description Default settings for this model */
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default_settings?: components["schemas"]["MainModelDefaultSettings"] | null;
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/** @default normal */
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variant?: components["schemas"]["ModelVariantType"];
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/**
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* Format
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* @description Format of the provided checkpoint model
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* @default checkpoint
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* @enum {string}
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*/
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format: "checkpoint" | "bnb_quantized_nf4b";
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/**
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* Config Path
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* @description path to the checkpoint model config file
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*/
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config_path: string;
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/**
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* Converted At
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* @description When this model was last converted to diffusers
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*/
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converted_at?: number | null;
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/** @default epsilon */
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prediction_type?: components["schemas"]["SchedulerPredictionType"];
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/**
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* Upcast Attention
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* @default false
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*/
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upcast_attention?: boolean;
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};
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/**
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* MainCheckpointConfig
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* @description Model config for main checkpoint models.
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@ -9761,11 +9864,11 @@ export type components = {
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variant?: components["schemas"]["ModelVariantType"];
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/**
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* Format
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* @description Format of the provided checkpoint model
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* @default checkpoint
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* @constant
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* @enum {string}
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*/
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format: "checkpoint";
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format: "checkpoint" | "bnb_quantized_nf4b";
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/**
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* Config Path
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* @description path to the checkpoint model config file
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@ -10670,7 +10773,7 @@ export type components = {
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* @description Storage format of model.
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* @enum {string}
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*/
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ModelFormat: "diffusers" | "checkpoint" | "lycoris" | "onnx" | "olive" | "embedding_file" | "embedding_folder" | "invokeai" | "t5_encoder" | "t5_encoder_8b" | "t5_encoder_4b";
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ModelFormat: "diffusers" | "checkpoint" | "lycoris" | "onnx" | "olive" | "embedding_file" | "embedding_folder" | "invokeai" | "t5_encoder" | "t5_encoder_8b" | "t5_encoder_4b" | "bnb_quantized_nf4b";
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/** ModelIdentifierField */
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ModelIdentifierField: {
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/**
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@ -10970,7 +11073,7 @@ export type components = {
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* Config Out
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* @description After successful installation, this will hold the configuration object.
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*/
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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;
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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;
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/**
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* Inplace
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* @description Leave model in its current location; otherwise install under models directory
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@ -11056,7 +11159,7 @@ export type components = {
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* Config
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* @description The model's config
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*/
|
||||
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 */
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user