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https://github.com/invoke-ai/InvokeAI
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Rename default schedulers across the app
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@ -52,7 +52,7 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
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width: int = Field(default=512, multiple_of=8, gt=0, description="The width of the resulting image", )
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height: int = Field(default=512, multiple_of=8, gt=0, description="The height of the resulting image", )
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cfg_scale: float = Field(default=7.5, ge=1, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
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scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
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scheduler: SAMPLER_NAME_VALUES = Field(default="lms", description="The scheduler to use" )
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model: str = Field(default="", description="The model to use (currently ignored)")
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# fmt: on
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@ -140,7 +140,7 @@ class TextToLatentsInvocation(BaseInvocation):
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noise: Optional[LatentsField] = Field(description="The noise to use")
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steps: int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
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cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
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scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
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scheduler: SAMPLER_NAME_VALUES = Field(default="lms", description="The scheduler to use" )
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model: str = Field(default="", description="The model to use (currently ignored)")
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seamless: bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
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seamless_axes: str = Field(default="", description="The axes to tile the image on, 'x' and/or 'y'")
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@ -634,7 +634,7 @@ class Args(object):
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choices=SAMPLER_CHOICES,
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metavar="SAMPLER_NAME",
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help=f'Set the default sampler. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
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default="k_lms",
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default="lms",
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)
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render_group.add_argument(
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"--log_tokenization",
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@ -142,7 +142,7 @@ class Generate:
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model=None,
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conf="configs/models.yaml",
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embedding_path=None,
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sampler_name="k_lms",
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sampler_name="lms",
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ddim_eta=0.0, # deterministic
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full_precision=False,
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precision="auto",
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@ -20,7 +20,7 @@ export const iterationGraph = {
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model: '',
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progress_images: false,
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prompt: 'dog',
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sampler_name: 'k_lms',
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sampler_name: 'lms',
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seamless: false,
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steps: 11,
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type: 'txt2img',
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@ -51,7 +51,7 @@ export const initialGenerationState: GenerationState = {
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perlin: 0,
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prompt: '',
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negativePrompt: '',
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sampler: 'k_lms',
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sampler: 'lms',
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seamBlur: 16,
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seamSize: 96,
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seamSteps: 30,
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@ -23,7 +23,7 @@
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],
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"threshold": 0,
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"postprocessing": null,
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"sampler": "k_lms",
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"sampler": "lms",
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"variations": [],
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"type": "txt2img"
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}
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@ -17,7 +17,7 @@ valid_metadata = {
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"width": 512,
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"height": 512,
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"cfg_scale": 7.5,
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"scheduler": "k_lms",
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"scheduler": "lms",
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"model": "stable-diffusion-1.5",
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},
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}
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