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RealVisXLV4

GenerativeModel
DashAI.back.models.hugging_face.RealVisXLV4

RealVisXL V4.0 photorealistic SDXL checkpoint.

Downloads its checkpoint into the component's own download folder.

Parameters​

negative_prompt
num_inference_steps : integer, default=25
Number of denoising steps to run. More steps refine the image but increase generation time. Typical range: 20-30 for fast results, 40-50 for higher quality. SDXL achieves good results with 25-40 steps.
guidance_scale : number, default=7.0
Classifier-Free Guidance (CFG) scale. Controls how strictly the image follows the text prompt. Low values (1-4) allow creative freedom; medium values (5-9) balance quality and adherence; high values (10+) enforce the prompt but may produce artifacts. SDXL works well with values between 5-9.
device : string, default=CPU
Hardware device for inference. Select a GPU option for hardware acceleration, strongly recommended for SDXL. CPU inference is very slow for this large model; expect 10-30 minutes per image on CPU.
seed : integer, default=-1
Random seed for reproducible generation. A fixed positive integer will always produce the same image for identical settings. Use a negative value (e.g. -1) for a random seed on each run.
width : integer, default=1024
Width of the output image in pixels. Must be a multiple of 8. SDXL's native resolution is 1024x1024 px. Using non-native resolutions may reduce quality.
height : integer, default=1024
Height of the output image in pixels. Must be a multiple of 8. SDXL's native resolution is 1024x1024 px.
num_images_per_prompt : integer, default=1
How many images to generate from a single prompt in one batch. Increasing this value is more efficient than running multiple sessions, but requires proportionally more GPU memory.

Methods​

component_dir(cls) -> pathlib.Path

Defined on DownloadableMixin

Return this component's own storage directory.

Returns

pathlib.Path
<COMPONENT_PATH>/<ClassName>.

delete(cls) -> None

Defined on DownloadableMixin

Remove the component's downloaded artifacts.

download(cls, report: Optional[Callable[[Optional[float], Optional[str]], NoneType]] = None) -> None

Defined on HFDownloadableMixin

Download all repos listed in hf_repos() into component_dir().

Parameters

report : ProgressReporter, optional
Callback invoked before each repo download with report(None, "Downloading <repo_id>"). None means no progress reporting.

generate(self, input: str) -> List[Any]

Defined on StableDiffusionXLGenerationModel

Generate images from a text prompt.

Parameters

input : str
Text prompt to generate an image from.

Returns

List[Any]
Generated output images in a list.

get_metadata(cls) -> Dict[str, Any]

Defined on BaseGenerativeModel

Get metadata values for the current generative model.

Returns

Dict[str, Any]
Dictionary indicating whether the model requires a download before use and the expected download size in bytes.

get_schema(cls) -> dict

Defined on ConfigObject

Generates the component related Json Schema.

Returns

dict
Dictionary representing the Json Schema of the component.

hf_repos(cls)

Defined on HFPretrainedDownloadMixin

Derive the single repo entry from MODEL_NAME.

Returns

list of tuple of (str, str)
[(MODEL_NAME, "model")] or an empty list when unset.

is_downloaded(cls) -> bool

Defined on HFDownloadableMixin

Return whether all repo directories exist and are non-empty.

Returns

bool
True when every repo listed in hf_repos() has a non-empty local directory; False otherwise (including when the list is empty).

validate_and_transform(self, raw_data: dict) -> dict

Defined on ConfigObject

It takes the data given by the user to initialize the model and returns it with all the objects that the model needs to work.

Parameters

raw_data : dict
A dictionary with the data provided by the user to initialize the model.

Returns

dict
A validated dictionary with the necessary objects.

Compatible with​