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4x-Ultrasharp

4x-Ultrasharp

4x-UltraSharp is a high-quality upscaling model available on Mage.Space, enhancing images with Kim2091's technology, compatible with Stable Diffusion via simple installation steps.
Author:LoRA
Inclusion Time:23 Jan 2025
Downloads:8807
Pricing Model:Free
Size:63.86 MB
Version:4x-UltraSharp v1.0
Introduction

Mage.Space offers a variety of exclusive models: AniMage PXL, AniReal PXL, Lucid Dream, AniMage SD1.5, Realistic Portrait SDXL - Pony, AniVerse PXL, AniMerge PXL, AniToon PXL, AniMics PXL, AniVerse XL SD1.5, AniVerse, AniThing, AniMerge, AniMesh, AniToon, AniMics.

We also partner with Shakker.ai.

This upgrader was not developed by us, all credit goes to Kim2091.

Installation method:

1. Rename the file to 4x-Ultrasharp .pth.

2. Copy the 4x-Ultrasharp .pth file to the "YOURSTABLEDIFFUSION_FOLDERmodelsESRGAN" folder.

3. Restart Stable Diffusion.

4. You can now find the new upgrader in the Extras tab.

Preview
FAQ

What to do if the model download fails?

Check whether the network connection is stable, try using a proxy or mirror source; confirm whether you need to log in to your account or provide an API key. If the path or version is wrong, the download will fail.

Why can't the model run in my framework?

Make sure you have installed the correct version of the framework, check the version of the dependent libraries required by the model, and update the relevant libraries or switch the supported framework version if necessary.

What to do if the model loads slowly?

Use a local cache model to avoid repeated downloads; or switch to a lighter model and optimize the storage path and reading method.

What to do if the model runs slowly?

Enable GPU or TPU acceleration, use batch data processing methods, or choose a lightweight model such as MobileNet to increase speed.

Why is there insufficient memory when running the model?

Try quantizing the model or using gradient checkpointing to reduce the memory requirements. You can also use distributed computing to spread the task across multiple devices.

What should I do if the model output is inaccurate?

Check whether the input data format is correct, whether the preprocessing method matching the model is in place, and if necessary, fine-tune the model to adapt to specific tasks.

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