58 lines
1.4 KiB
Markdown
58 lines
1.4 KiB
Markdown
## Run benchmark
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### Using GSM8K Platinum
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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:
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```
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python3 bench_sglang.py --num-shots 8 --num-questions 1209 --parallel 1209 --platinum
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```
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For more information, see: https://huggingface.co/datasets/madrylab/gsm8k-platinum
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### Benchmark sglang
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```
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python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000
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```
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```
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python3 bench_sglang.py --num-questions 200
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```
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### Benchmark vllm
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```
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python3 -m vllm.entrypoints.api_server --tokenizer-mode auto --model meta-llama/Llama-2-7b-chat-hf --disable-log-requests --port 21000
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```
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```
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python3 bench_other.py --num-questions 200 --backend vllm
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```
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### Benchmark lightllm
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```
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# A10G
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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
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```
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```
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python3 bench_other.py --num-questions 200 --backend lightllm
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```
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### Benchmark guidance
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```
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python3 bench_other.py --num-questions 200 --backend guidance --parallel 1 --n-ctx 4096 --model-path path/to/gguf
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```
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### Benchmark lmql
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```
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CUDA_VISIBLE_DEVICES=0,1 lmql serve-model meta-llama/Llama-2-7b-chat-hf --cuda --port 23000
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```
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```
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python3 bench_other.py --num-questions 100 --backend lmql --parallel 2
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```
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