# Serving a model
## Serving [LLaMA-2](https://github.com/facebookresearch/llama)
You can download [llama-2 models from huggingface](https://huggingface.co/meta-llama) and serve them like below:
7B
```shell
lmdeploy convert llama2 /path/to/llama-2-7b-chat-hf
bash workspace/service_docker_up.sh
```
13B
```shell
lmdeploy convert llama2 /path/to/llama-2-13b-chat-hf --tp 2
bash workspace/service_docker_up.sh
```
70B
```shell
lmdeploy convert llama2 /path/to/llama-2-70b-chat-hf --tp 8
bash workspace/service_docker_up.sh
```
## 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)
7B
```shell
lmdeploy convert llama /path/to/llama-7b llama \
--tokenizer_path /path/to/tokenizer/model
bash workspace/service_docker_up.sh
```
13B
```shell
lmdeploy convert llama /path/to/llama-13b llama \
--tokenizer_path /path/to/tokenizer/model --tp 2
bash workspace/service_docker_up.sh
```
30B
```shell
lmdeploy convert llama /path/to/llama-30b llama \
--tokenizer_path /path/to/tokenizer/model --tp 4
bash workspace/service_docker_up.sh
```
65B
```shell
lmdeploy convert llama /path/to/llama-65b llama \
--tokenizer_path /path/to/tokenizer/model --tp 8
bash workspace/service_docker_up.sh
```
### Serving [Vicuna](https://lmsys.org/blog/2023-03-30-vicuna/)
7B
```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
lmdeploy convert vicuna /path/to/vicuna-7b
bash workspace/service_docker_up.sh
```
13B
```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
lmdeploy convert vicuna /path/to/vicuna-13b
bash workspace/service_docker_up.sh
```