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doc: fix FaqGen/README.md markdown (#478)
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* fix multiple H1 headings

Signed-off-by: David B. Kinder <[email protected]>
Co-authored-by: Abolfazl Shahbazi <[email protected]>
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dbkinder and ashahba authored Jul 31, 2024
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Expand Up @@ -4,14 +4,14 @@ In today's data-driven world, organizations across various industries face the c

Our FAQ Generation Application leverages the power of large language models (LLMs) to revolutionize the way you interact with and comprehend complex textual data. By harnessing cutting-edge natural language processing techniques, our application can automatically generate comprehensive and natural-sounding frequently asked questions (FAQs) from your documents, legal texts, customer queries, and other sources. In this example use case, we utilize LangChain to implement FAQ Generation and facilitate LLM inference using Text Generation Inference on Intel Xeon and Gaudi2 processors.

# Deploy FAQ Generation Service
## Deploy FAQ Generation Service

The FAQ Generation service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
The FAQ Generation service can be deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.

## Deploy FAQ Generation on Gaudi
### Deploy FAQ Generation on Gaudi

Refer to the [Gaudi Guide](./docker/gaudi/README.md) for instructions on deploying FAQ Generation on Gaudi.

## Deploy FAQ Generation on Xeon
### Deploy FAQ Generation on Xeon

Refer to the [Xeon Guide](./docker/xeon/README.md) for instructions on deploying FAQ Generation on Xeon.

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