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Signed-off-by: lvliang-intel <[email protected]>

templates/gaudi-rag/README.md

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 # Gaudi RAG
 This template performs RAG using Chroma and Text Generation Inference on Habana Gaudi/Gaudi2.
-The Intel Gaudi 2 accelerator supports both deep learning training and inference for AI models like LLMs. The Intel Gaudi 2 accelerator is built on a 7nm process technology. It has a heterogeneous compute architecture that includes dual matrix multiplication engines (MME) and 24 programmable tensor processor cores (TPC). When compared to popular cloud accelerators in the same generation, such as the NVIDIA A100-40GB and A100-80GB, the Gaudi 2 has more memory (96GB of HBM2E), higher memory bandwidth, and higher peak FLOP/s. Note that the AMD MI250 has higher specs per chip but comes in smaller system configurations of only 4xMI250. Gaudi2 is about twice faster than Nvidia A100 80GB for both training and inference, please check[intel-gaudi-2-benchmark](https://www.databricks.com/blog/llm-training-and-inference-intel-gaudi2-ai-accelerators)
+The Intel Gaudi 2 accelerator supports both deep learning training and inference for AI models like LLMs. The Intel Gaudi 2 accelerator is built on a 7nm process technology. It has a heterogeneous compute architecture that includes dual matrix multiplication engines (MME) and 24 programmable tensor processor cores (TPC). When compared to popular cloud accelerators in the same generation, such as the NVIDIA A100-40GB and A100-80GB, the Gaudi 2 has more memory (96GB of HBM2E), higher memory bandwidth, and higher peak FLOP/s. Note that the AMD MI250 has higher specs per chip but comes in smaller system configurations of only 4xMI250. Gaudi2 is about twice faster than Nvidia A100 80GB for both training and inference, please check [intel-gaudi-2-benchmark](https://www.databricks.com/blog/llm-training-and-inference-intel-gaudi2-ai-accelerators).
 
 ## Environment Setup
 To use [🤗 text-generation-inference](https://github.com/huggingface/text-generation-inference) on Habana Gaudi/Gaudi2, please follow these steps: