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add example for Llama3 vllm server #404

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add readme
cameron-chen committed Oct 13, 2024
commit 5a3d4a6d6499e5990b2944c54194bc78dbfe4db5
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# Annotator Served by vLLM

This config demonstrates how to utilize an annotator served by vLLM. This brings some advantages:
- Allow users to use "weighted"-style annotator, similar to `weighted_alpaca_eval_gpt4_turbo`;
- One vLLM server can support multiple nodes in a cluster environment;
- Easy setup using vLLM's OpenAI-compatible APIs.

## Setup
1. Start the vLLM Server:

```bash
vllm serve /home/shared/Meta-Llama-3-70B-Instruct --dtype auto --api-key token-abc123
```

2. Create the client config `local_configs.yaml` in `client_configs` folder:

```bash
default:
- api_key: "token-abc123"
base_url: "http://localhost:8000/v1"
```

3. Run evaluation:

```bash
export OPENAI_CLIENT_CONFIG_PATH=<path to local_configs.yaml>
alpaca_eval evaluate --model_outputs 'example/outputs.json' --annotators_config weighted_alpaca_eval_vllm_llama3_70b
```