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doc: update readme acknowledgment. #2

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12 changes: 6 additions & 6 deletions README.md
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Expand Up @@ -174,12 +174,12 @@ Welcome to contact us:
## 7. Acknowledgment

This project was made possible thanks to the following open-source projects:
- [ScaleLLM](https://github.com/vectorch-ai/ScaleLLM) - Adopt the graph construction and runtime execution from ScaleLLM.
- [MindIE](https://www.hiascend.com/en/software/mindie) - Adopt the kernel optimization and ATB from MindIE.
- [Mooncake](https://github.com/kvcache-ai/Mooncake) - Adopt the hybrid KV cache management from Mooncake.
- [brpc](https://github.com/apache/brpc) - Build the high-performance http service with brpc.
- [tokenizers-cpp](https://github.com/mlc-ai/tokenizers-cpp) - Adopt the tokenizers-cpp for c++ tokenizer.
- [safetensors](https://github.com/huggingface/safetensors) - Adopt the safetensors for model weights loading.
- [ScaleLLM](https://github.com/vectorch-ai/ScaleLLM) - xLLM draws inspiration from ScaleLLM's graph construction method and references its runtime execution.
- [MindIE](https://www.hiascend.com/en/software/mindie) - Develop xLLM kernels based on kernel optimization and ATB of MindIE.
- [Mooncake](https://github.com/kvcache-ai/Mooncake) - Build xLLM hybrid KV cache management based on Mooncake.
- [brpc](https://github.com/apache/brpc) - Build high-performance http service based on brpc.
- [tokenizers-cpp](https://github.com/mlc-ai/tokenizers-cpp) - Build C++ tokenizer based on tokenizers-cpp.
- [safetensors](https://github.com/huggingface/safetensors) - xLLM relies on the C binding safetensors capability.


Thanks to all the following [developers](https://github.com/jd-opensource/xllm/graphs/contributors) who have contributed to xLLM.
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