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LISRec-MFilter

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This PR significantly enhances the model card for LISRec-MFilter by:

• Adding pipeline_tag: text-retrieval to accurately categorize the model's primary function in sequential recommendation on the Hub.
• Specifying library_name: transformers to enable the automated "how to use" widget, as evidenced by the config.json (model_type: "t5", transformers_version) and the use of T5 components as per the GitHub repository.
• Adding relevant tags: [recommendation, sequential-recommendation] for better discoverability.
• Providing a concise yet comprehensive description of the model, summarizing its purpose and key features.
• Including a direct link to the paper on Hugging Face Papers: LISRec: Modeling User Preferences with Learned Item Shortcuts for Sequential Recommendation.
• Embedding the model's architectural image from the GitHub repository.
• Adding a link to the official GitHub repository for full code, installation, and usage details.
• Including the BibTeX citation and acknowledgements from the GitHub README.

These updates aim to make the model more discoverable, understandable, and easier to use for researchers and developers on Hugging Face.