Update README.md

README.md

@@ -31,13 +31,12 @@ We present Kimi-Audio, an open-source audio foundation model excelling in **audi
 Kimi-Audio is designed as a universal audio foundation model capable of handling a wide variety of audio processing tasks within a single unified framework. Key features include:
 
 *   **Universal Capabilities:** Handles diverse tasks like speech recognition (ASR), audio question answering (AQA), audio captioning (AAC), speech emotion recognition (SER), sound event/scene classification (SEC/ASC) and end-to-end speech conversation.
-*   **State-of-the-Art Performance:** Achieves SOTA results on numerous audio benchmarks (see our [Technical Report](https://raw.githubusercontent.com/MoonshotAI/Kimi-Audio/main/assets/kimia_report.pdf)). <!-- TODO: Replace with actual raw PDF URL -->
+*   **State-of-the-Art Performance:** Achieves SOTA results on numerous audio benchmarks (see our [Technical Report](https://raw.githubusercontent.com/MoonshotAI/Kimi-Audio/master/assets/kimia_report.pdf)).
 *   **Large-Scale Pre-training:** Pre-trained on over 13 million hours of diverse audio data (speech, music, sounds) and text data.
 *   **Novel Architecture:** Employs a hybrid audio input (continuous acoustic + discrete semantic tokens) and an LLM core with parallel heads for text and audio token generation.
 *   **Efficient Inference:** Features a chunk-wise streaming detokenizer based on flow matching for low-latency audio generation.
 
-For more details, please refer to our [GitHub Repository](https://github.com/MoonshotAI/Kimi-Audio) and [Technical Report](https://raw.githubusercontent.com/MoonshotAI/Kimi-Audio/main/assets/kimia_report.pdf). <!-- TODO: Replace with actual raw PDF URL -->
-<br>
+For more details, please refer to our [GitHub Repository](https://github.com/MoonshotAI/Kimi-Audio) and [Technical Report](https://raw.githubusercontent.com/MoonshotAI/Kimi-Audio/master/assets/kimia_report.pdf).
 
 ## Requirements