Update README.md

README.md

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 # Seed-Coder-8B-Base
 
 ## Introduction
+We are thrilled to introduce Seed-Coder, a powerful, transparent, and parameter-efficient family of open-source code models at the 8B scale, featuring base, instruct, and reasoning variants. Seed-Coder contributes to promote the evolution of open code models through the following highlights.
+
+- Model-centric: Seed-Coder predominantly leverages LLMs instead of hand-crafted rules for code data filtering, minimizing manual effort in pretraining data construction.
+- Transparent: We openly share detailed insights into our model-centric data pipeline, including methods for curating GitHub data, commits data, and code-related web data.
+- Powerful: Seed-Coder achieves state-of-the-art performance among open-source models of comparable size across a diverse range of coding tasks.
+
+
+## Highlight
+
+
 **Seed-Coder-8B-Base** is an 8-billion-parameter foundation model tailored for code understanding and generation. It is designed to provide developers with a powerful, general-purpose code model capable of handling a wide range of coding tasks. It features: 
-- Pretrained on a **massively curated corpus**, filtered using **LLM-based techniques** to ensure **high-quality real-world code**, **text-code alignment data**, and **synthetic datasets**, resulting in cleaner and more effective learning signals.
+- Pretrained on a **massively curated corpus**, filtered using **LLM-based techniques** to ensure high-quality real-world code, resulting in cleaner and more effective learning signals.
 - Excels at **code completion** and supports **Fill-in-the-Middle (FIM)** tasks, enabling it to predict missing code spans given partial contexts.
 - Robust performance across **various programming languages** and **code reasoning scenarios**, making it ideal for downstream finetuning or direct use in code generation systems.
 - **Long-context support** up to 32K tokens, enabling it to handle large codebases, multi-file projects, and extended editing tasks.