feat: support DAT

[Tohrusky]

Summary by Sourcery

Add support for DAT models and update core binary download URLs to the latest release version.

New Features:

• Add support for multiple DAT model options in the ModelOptions.ts file.

Enhancements:

• Update download URLs for macOS and Windows core binaries to a new release version in download-core.js.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR adds support for DAT (Dual Aggregation Transformer) models by adding new model options and updating the core download URLs. The implementation involves adding various DAT model configurations with different scaling factors and variants (standard, light, and APISR GAN) to the model options list, and updating the core binary download links to a newer release.

Class diagram for updated ModelOptions

classDiagram
    class ModelOptions {
        +String label
        +String value
    }

    ModelOptions : +DAT_S_2x
    ModelOptions : +DAT_S_3x
    ModelOptions : +DAT_S_4x
    ModelOptions : +DAT_2x
    ModelOptions : +DAT_3x
    ModelOptions : +DAT_4x
    ModelOptions : +DAT_2_2x
    ModelOptions : +DAT_2_3x
    ModelOptions : +DAT_2_4x
    ModelOptions : +DAT_light_2x
    ModelOptions : +DAT_light_3x
    ModelOptions : +DAT_light_4x
    ModelOptions : +DAT_APISR_GAN_generator_4x
    note for ModelOptions "New DAT model options added"

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File-Level Changes

Change	Details	Files
Added DAT model options with various configurations	Added standard DAT models with 2x, 3x, and 4x scaling factors Added DAT_S (small) variants with 2x, 3x, and 4x scaling factors Added DAT_2 variants with 2x, 3x, and 4x scaling factors Added light variants with 2x, 3x, and 4x scaling factors Added DAT APISR GAN generator model with 4x scaling	src/renderer/src/utils/ModelOptions.ts
Updated core binary download URLs	Updated download URLs from 2024-11-08 to 2024-11-09 release Updated URLs for macos-arm64, macos-x64, and windows-x64 platforms	resources/download-core.js

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[sourcery-ai]

Hey @Tohrusky - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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