chore: vendor sglang v0.5.10 snapshot

third_party/sglang/benchmark/gsm8k/README.md

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+## Run benchmark
+
+### Using GSM8K Platinum
+
+GSM8K Platinum is a revised version of the GSM8K test set with corrected labels and removed ambiguous questions. It can be more stable than the original GSM8K dataset. It's a drop-in replacement that can be used by adding the `--platinum` flag:
+
+```
+python3 bench_sglang.py --num-shots 8 --num-questions 1209 --parallel 1209 --platinum
+```
+
+For more information, see: https://huggingface.co/datasets/madrylab/gsm8k-platinum
+
+### Benchmark sglang
+```
+python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000
+```
+
+```
+python3 bench_sglang.py --num-questions 200
+```
+
+
+### Benchmark vllm
+```
+python3 -m vllm.entrypoints.api_server --tokenizer-mode auto --model meta-llama/Llama-2-7b-chat-hf --disable-log-requests --port 21000
+```
+
+```
+python3 bench_other.py --num-questions 200 --backend vllm
+```
+
+
+### Benchmark lightllm
+```
+# A10G
+python -m lightllm.server.api_server --tokenizer_mode auto --model_dir ~/model_weights/llama-2-7b-chat-hf --max_total_token_num 16000 --port 22000
+```
+
+```
+python3 bench_other.py --num-questions 200 --backend lightllm
+```
+
+
+### Benchmark guidance
+```
+python3 bench_other.py --num-questions 200 --backend guidance --parallel 1 --n-ctx 4096 --model-path path/to/gguf
+```
+
+
+### Benchmark lmql
+```
+CUDA_VISIBLE_DEVICES=0,1 lmql serve-model meta-llama/Llama-2-7b-chat-hf --cuda --port 23000
+```
+
+```
+python3 bench_other.py --num-questions 100 --backend lmql --parallel 2
+```