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mdeberta-v3-base-subjectivity-sentiment-multilingual

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This PR significantly enhances the model card by:

• Updating the license to cc-by-4.0 as indicated in the official GitHub repository.
• Adding the pipeline_tag: text-classification for improved discoverability and direct usage via transformers pipelines.
• Enriching tags with relevant keywords like subjectivity-detection, multilingual, sentiment, news, and mdeberta-v3.
• Adding language tags for all supported languages (Arabic, German, English, Italian, Bulgarian, Greek, Polish, Romanian, Ukrainian).
• Adding datasets tag for clef-2025-checkthat-lab-task-1-subjectivity.
• Populating the "Model description", "Intended uses & limitations", and "Training and evaluation data" sections with comprehensive details extracted from the paper abstract and the GitHub README.
• Adding direct links to the official GitHub repository and the Hugging Face collection related to the project.
• Including a clear "How to use" code snippet for easy model inference.
• Adding a BibTeX "Citation" for the associated paper.

These updates provide a much richer and more user-friendly model card, improving clarity, discoverability, and adherence to Hugging Face Hub best practices.