README.md

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## Introduction

## Installation

Below are quick steps for installation:

```shell
conda create -n open-mmlab python=3.8
conda activate open-mmlab
git clone https://github.com/open-mmlab/llmdeploy.git
cd llmdeploy
pip install -e .
```

## Quick Start

### Serving [LLaMA](https://github.com/facebookresearch/llama)

Weights for the LLaMA models can be obtained from by filling out [this form](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform?usp=send_form)

Run one of the following commands to serve a LLaMA model on NVIDIA GPU server:

<details open>
<summary><b>7B</b></summary>

```shell
python3 llmdeploy/serve/fastertransformer/deploy.py llama-7B /path/to/llama-7b llama \
    --tokenizer_path /path/to/tokenizer/model
bash workspace/service_docker_up.sh
```

</details>

<details open>
<summary><b>13B</b></summary>

```shell
python3 llmdeploy/serve/fastertransformer/deploy.py llama-13B /path/to/llama-13b llama \
    --tokenizer_path /path/to/tokenizer/model --tp 2
bash workspace/service_docker_up.sh
```

</details>

<details open>
<summary><b>33B</b></summary>

```shell
python3 llmdeploy/serve/fastertransformer/deploy.py llama-33B /path/to/llama-33b llama \
    --tokenizer_path /path/to/tokenizer/model --tp 4
bash workspace/service_docker_up.sh
```

</details>

<details open>
<summary><b>65B</b></summary>

```shell
python3 llmdeploy/serve/fastertransformer/deploy.py llama-65B /path/to/llama-65b llama \
    --tokenizer_path /path/to/tokenizer/model --tp 8
bash workspace/service_docker_up.sh
```

</details>

### Serving [Vicuna](https://lmsys.org/blog/2023-03-30-vicuna/)

<details open>
<summary><b>7B</b></summary>

```shell
python3 -m pip install fschat
python3 -m fastchat.model.apply_delta \
  --base-model-path /path/to/llama-7b \
  --target-model-path /path/to/vicuna-7b \
  --delta-path lmsys/vicuna-7b-delta-v1.1

python3 llmdeploy/serve/fastertransformer/deploy.py vicuna-7B /path/to/vicuna-7b hf
bash workspace/service_docker_up.sh
```

</details>

<details>
<summary><b>13B</b></summary>

```shell
python3 -m pip install fschat
python3 -m fastchat.model.apply_delta \
  --base-model-path /path/to/llama-13b \
  --target-model-path /path/to/vicuna-13b \
  --delta-path lmsys/vicuna-13b-delta-v1.1

python3 llmdeploy/serve/fastertransformer/deploy.py vicuna-13B /path/to/vicuna-13b hf
bash workspace/service_docker_up.sh
```

</details>

## Inference with Command Line Interface

```shell
python3 llmdeploy/serve/client.py {server_ip_addresss}:33337 1
```

## Contributing

We appreciate all contributions to LLMDeploy. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guideline.

## Acknowledgement

- [FasterTransformer](https://github.com/NVIDIA/FasterTransformer)

## License

This project is released under the [Apache 2.0 license](LICENSE).