Update README.md

README.md

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+Our project, Polyglot, aims to bridge the linguistic gap in NLP and supplement the field's current shortcomings by creating efficient foundation models for low-resource languages.
+
 In recent years, generative AI has seen remarkable advancements, with foundation models emerging as the cornerstone of much of the research and development in the field. However, the prevailing deep learning paradigm demands vast resources in terms of data and computation. This data-intensive approach has inadvertently deepened the divide between high-resource and low-resource languages. High-resource languages benefit from the bulk of development efforts and readily available resources, while low-resource languages face significant challenges in achieving comparable performance and autonomy.
 
 To foster a more equitable, sustainable, and open ecosystem for AI research and development, we aim to create tools and resources to support the development of foundation models for low-resource languages. This includes developing models, datasets, and open-source code to empower underrepresented linguistic communities.
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 - Demo on how to [run inference on ViTucano](https://colab.research.google.com/drive/110_Gtjgu4pldRQP864_Y-rSm2VhyW7Li).
 - Demo on how to [run inference on Tucano](https://colab.research.google.com/drive/1Qf2DsFOFDA7RKkamI-tH3OregtOlZ8Cz).
 - Demo on how to create a simple [Chat UI for Tucano](https://colab.research.google.com/drive/1fEW10CXksMfMv1veLr22OESwDs6e-W1b) using Gradio.
-- [Tucano OpenVINO](https://huggingface.co/cabelo/Tucano-2b4-Instruct-fp16-ov) is a ported version of Tucano-2b4-Instruct optimized for Intel openVINO inference technology.
+- [Tucano OpenVINO](https://huggingface.co/cabelo/Tucano-2b4-Instruct-fp16-ov) is a ported version of Tucano-2b4-Instruct optimized for Intel openVINO inference technology.
+
+**Polyglot is a project funded by the Federal Ministry of Education and Research (BMBF) and the Ministry of Culture and Science of the State of North Rhine-Westphalia (MWK) as part of TRA Sustainable Futures (University of Bonn) and the Excellence Strategy of the federal and state governments.**