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Signed-off-by: kerthcet <[email protected]>

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README.md

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 # llmaz
 
-☸️ Effortlessly operating LLMs on Kubernetes, e.g. Serving.
+[![stability-wip](https://img.shields.io/badge/stability-wip-lightgrey.svg)](https://github.com/mkenney/software-guides/blob/master/STABILITY-BADGES.md#work-in-progress)
+[![GoReport Widget]][GoReport Status]
+[![Latest Release](https://img.shields.io/github/v/release/inftyai/llmaz?include_prereleases)](https://github.com/inftyai/llmaz/releases/latest)
+
+[GoReport Widget]: https://goreportcard.com/badge/github.com/inftyai/llmaz
+[GoReport Status]: https://goreportcard.com/report/github.com/inftyai/llmaz
+
+llmaz, pronounced as `/lima:z/`, aims to provide a production-ready inference platform for various LLMs on Kubernetes. It tightly integrates with state-of-the-art inference backends, such as [vLLM](https://github.com/vllm-project/vllm).
+
+## Concept
+
+![image](./docs/assets/overview.png)
+
+## Feature Overview
+
+- **Easy to use**: People can deploy a production-ready LLM service with minimal configurations.
+- **High performance**: llmaz integrates with vLLM by default for high performance inference. Other backend supports are on the way.
+- **Autoscaling efficiently**: llmaz works smoothly with autoscaling components like [cluster-autoscaler](https://github.com/kubernetes/autoscaler/tree/master/cluster-autoscaler) and [Karpenter](https://github.com/kubernetes-sigs/karpenter) to support elastic scenarios.
+- **Model as the first citizen**: Cloud providers or model providers can manage the models breezily.
+- **Accelerator fungibility**: llmaz supports serving LLMs with different accelerators for the sake of cost and performance.
+- **SOTA inference technologies**: llmaz support the latest SOTA technologies like [speculative decoding](https://arxiv.org/abs/2211.17192) and [Splitwise](https://arxiv.org/abs/2311.18677).
+
+## Quick Start
+
+Refer to the [samples](/config/samples/) for quick deployment.
+
+## Roadmap
+
+- Metrics support
+- Autoscaling support
+- Gateway support
+- Serverless support
+- CLI tool
+- Model training, fine tuning in the long-term.
+
+## Contributions
+
+🚀 All kinds of contributions are welcomed ! Please follow [Contributing](https://github.com/InftyAI/community/blob/main/CONTRIBUTING.md).
+
+## Contributors
+
+🎉 Thanks to all these contributors.
+
+<a href="https://github.com/InftyAI/llmaz/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=InftyAI/llmaz" />
+</a>