Kr1sJ

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iMontage

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This PR significantly enhances the model card for iMontage by adding comprehensive information and metadata.

Key updates include:

• Adding the pipeline_tag: image-to-image for better discoverability on the Hub, as the model is an all-in-one image generator.
• Specifying library_name: diffusers due to the model's compatibility and usage of diffusion_pytorch_model.safetensors as seen in the installation instructions. This enables the automated "how to use" widget.
• Including a link to the paper: iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation.
• Linking to the official project page: https://kr1sjfu.github.io/iMontage-web/.
• Providing a link to the GitHub repository: https://github.com/Kr1sJFU/iMontage.
• Incorporating a "Features" section and a "Sample Usage" section with a Python code snippet extracted directly from the GitHub README, demonstrating basic image generation.
• Adding a table illustrating various inference tasks with example inputs and outputs, sourced from the GitHub README.
• Including the "Acknowledgment" and "Citation" sections.

Please review and merge this PR if everything looks good.