post-describe-style-inferences
Analyzes images or AI models to identify and describe their visual style characteristics for creative applications.
Instructions
Describe the style of the given images or models.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dryRun | No | ||
| ensureIPCleared | No | Whether we try to ensure IP removal for new prompt generation. | |
| images | No | ||
| seed | No | If specified, the API will make a best effort to produce the same results, such that repeated requests with the same `seed` and parameters should return the same outputs. Must be used along with the same parameters including prompt, model's state, etc.. | |
| unwantedSequences | No | ||
| modelId | No | The modelId used to condition the generation. When provided, the generation will take into account model's training images, examples. In `contextual` mode, the modelId is used to retrieve additional context from the model such as its type and capabilities. | |
| temperature | No | The sampling temperature to use. Higher values like `0.8` will make the output more random, while lower values like `0.2` will make it more focused and deterministic. We generally recommend altering this or `topP` but not both. | |
| assetIds | No | ||
| topP | No | An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So `0.1` means only the tokens comprising the top `10%` probability mass are considered. We generally recommend altering this or `temperature` but not both. |