- To enable torchao quantization, add `--torchao-config int4wo-128`. It supports various quantization strategies.
- To enable fp8 weight quantization, add `--quantization fp8` on a fp16 checkpoint or directly load a fp8 checkpoint without specifying any arguments.
- To enable fp8 kv cache quantization, add `--kv-cache-dtype fp8_e5m2`.
- If the model does not have a chat template in the Hugging Face tokenizer, you can specify a [custom chat template](https://sglang.readthedocs.io/en/latest/custom_chat_template.html).
- If the model does not have a chat template in the Hugging Face tokenizer, you can specify a [custom chat template](https://sgl-project.github.io/custom_chat_template.html).
- To run tensor parallelism on multiple nodes, add `--nnodes 2`. If you have two nodes with two GPUs on each node and want to run TP=4, let `sgl-dev-0` be the hostname of the first node and `50000` be an available port, you can use the following commands. If you meet deadlock, please try to add `--disable-cuda-graph`
```
# Node 0
...
...
@@ -158,7 +158,7 @@ You can view the full example [here](https://github.com/sgl-project/sglang/tree/
Add unit tests under [sglang/test](../../test). You can learn how to add and run tests from the README.md in that folder.
Add unit tests under [sglang/test](https://github.com/sgl-project/sglang/tree/main/test). You can learn how to add and run tests from the README.md in that folder.
**NOTE**: There are two chat template systems in SGLang project. This document is about setting a custom chat template for the OpenAI-compatible API server (defined at [conversation.py](../../python/sglang/srt/conversation.py)). It is NOT related to the chat template used in the SGLang language frontend (defined at [chat_template.py](../../python/sglang/lang/chat_template.py)).
**NOTE**: There are two chat template systems in SGLang project. This document is about setting a custom chat template for the OpenAI-compatible API server (defined at [conversation.py](https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/conversation.py)). It is NOT related to the chat template used in the SGLang language frontend (defined at [chat_template.py](https://github.com/sgl-project/sglang/blob/main/python/sglang/lang/chat_template.py)).
By default, the server uses the chat template specified in the model tokenizer from Hugging Face.
It should just work for most official models such as Llama-2/Llama-3.