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README.md

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 💬 [Discord](https://discord.gg/Cx737yw4ed) | 😺 [GitHub](https://github.com/ai-twinkle) | 🤗 [Hugging Face](https://huggingface.co/twinkle-ai) | 🔗 [Linkedin](https://www.linkedin.com/company/twinkle-ai/) 
 
-🌟 **Twinkle AI** 是一個在 2024 年底誕生的繁中語言模型研究社群，起步於 Llama 開源模型，逐步打造出專屬於繁體中文的落地技術。社群成員來自各行各業，因熱愛模型訓練而聚，從蒐集繁中語料到模型訓練，本社群持績開源繁中訓練集文本以及繁中大語言模型。社群旨在用實際行動推廣大語言模型的訓練知識，並希望透過開放與共享，推動臺灣在生成式 AI 領域的發展。
+🌟 **Twinkle AI** is a Traditional Chinese language model research community founded in late 2024. Starting with the open-source LLaMA models, we are gradually building practical technologies tailored for Traditional Chinese. Our community is made up of people from all walks of life, united by a shared passion for model training. From collecting Traditional Chinese corpora to training language models, we are committed to open-sourcing both our datasets and our models.
 
-## 已開源項目
-- [Twinkle Eval](https://github.com/ai-twinkle/Eval)：高效且準確的 AI 評測工具，採用並行且隨機化測試方法，提供客觀的模型性能分析與穩定性評估，並支援多種常見評測數據集。
+Our mission is to promote knowledge of large language model training through real-world practices. By embracing openness and collaboration, we aim to advance Taiwan’s development in the field of generative AI.
 
-👋 歡迎加入社群 [Discord](https://discord.gg/Cx737yw4ed) 一起討論。
+### Open-Source Projects
+- **[Twinkle Eval](https://github.com/ai-twinkle/Eval)**: A fast and accurate AI evaluation tool that uses parallel and randomized testing methods to provide objective performance analysis and stability assessments. It supports various commonly used benchmark datasets.
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+👋 Join our [Discord](https://discord.gg/Cx737yw4ed) to connect and collaborate with the community!