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Sdxl Lora Customize Model


AI model preview image
The sdxl-lora-customize-model is a text-to-image AI model capable of creating high resolution visuals (1024x1024). LoRa models can be loaded through URLs to generate immediate outputs. It uses a certain set of parameters like width, height, prompt, refine, scheduler, lora scale, number of outputs, guidance scale, watermark application, high noise fraction, prompt strength, and number of inference steps to fine-tune the generated image. The output of the model are URLs of the generated images. Training can be done through a provided link.

Use cases

The sdxl-lora-customize-model is a text-to-image AI that can craft high-quality visuals that are relatively large in resolution. Possible use cases of this AI model could revolve around its ability to generate custom visuals based on descriptive text input. This could include generating unique graphics for fashion designers based on their clothing descriptions, or creating visual concepts for architects from project briefs. Considering its image-to-image tag, the model could also be used to transform and refine one image into another, which could be useful for graphic artists or game developers who need custom graphics but lack drawing skills. Furthermore, businesses in advertising could use this model to generate different images for their promotional materials based on specific key words or prompts. The technology could also potentially be used to develop tools and applications that could drastically impact the way individuals and industries create visual content. As the AI model supports high resolution images, it might find use in fields where detailed imagery is paramount, such as in medical imaging or satellite imagery.


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Avg run time

Creator Models

Controlnet V1 1 Multi$?1,927
Remove Object$?67,394
Sdxl Lora Customize Training$?7,055

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Summary of this model and related resources.

Model NameSdxl Lora Customize Model

Introducing a text-to-image AI that crafts stunning 1024x1024 visuals. Load...

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API SpecView on Replicate
Github LinkNo Github link provided
Paper LinkNo paper link provided


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