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vllm/benchmarks/run.sh
LiuXiaoxuanPKU bc3b20f81f accepted length code
2025-08-03 20:06:15 -07:00

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# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name sonnet \
# --dataset-path /data/lily/batch-sd/benchmarks/sonnet.txt \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name sharegpt \
# --dataset-path /data/lily/ShareGPT_V3_unfiltered_cleaned_split.json \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name hf \
# --dataset-path likaixin/InstructCoder \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name sonnet \
# --dataset-path /data/lily/batch-sd/benchmarks/sonnet.txt \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name sharegpt \
# --dataset-path /data/lily/ShareGPT_V3_unfiltered_cleaned_split.json \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3-8B-Instruct \
# --dataset-name hf \
# --dataset-path likaixin/InstructCoder \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path likaixin/InstructCoder \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle3", "model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
python benchmarks/benchmark_throughput.py \
--model meta-llama/Meta-Llama-3.1-8B-Instruct\
--dataset-name hf \
--dataset-path philschmid/mt-bench \
--prefix-len 0 \
--output-len 512 \
--num-prompts 200 \
--speculative_config '{"method": "eagle3", "model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name sharegpt \
# --dataset-path /data/lily/ShareGPT_V3_unfiltered_cleaned_split.json \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle3", "model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name sonnet \
# --dataset-path /data/lily/batch-sd/benchmarks/sonnet.txt \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle3", "model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path likaixin/InstructCoder \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name sharegpt \
# --dataset-path /data/lily/ShareGPT_V3_unfiltered_cleaned_split.json \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path likaixin/InstructCoder \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model deepseek-ai/DeepSeek-R1-Distill-Llama-8B \
# --dataset-name hf \
# --dataset-path AI-MO/aimo-validation-aime \
# --prefix-len 0 \
# --output-len 1024 \
# --num-prompts 90 \
# --speculative_config '{"method": "eagle3", "num_speculative_tokens": 20, "model": "yuhuili/EAGLE3-DeepSeek-R1-Distill-LLaMA-8B"}'
# python benchmarks/benchmark_throughput.py \
# --model deepseek-ai/DeepSeek-R1-Distill-Llama-8B \
# --dataset-name hf \
# --dataset-path AI-MO/aimo-validation-aime \
# --prefix-len 0 \
# --output-len 1024 \
# --num-prompts 90 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name sharegpt \
# --dataset-path /data/lily/ShareGPT_V3_unfiltered_cleaned_split.json \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path philschmid/mt-bench \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path philschmid/mt-bench \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path abisee/cnn_dailymail \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "eagle", "model": "yuhuili/EAGLE-LLaMA3-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path abisee/cnn_dailymail \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path philschmid/mt-bench \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 10 \
# --speculative_config '{"method": "eagle3", "model": "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", "num_speculative_tokens": 20}'
# python benchmarks/benchmark_throughput.py \
# --model meta-llama/Meta-Llama-3.1-8B-Instruct \
# --dataset-name hf \
# --dataset-path abisee/cnn_dailymail \
# --prefix-len 0 \
# --output-len 512 \
# --num-prompts 200 \
# --speculative_config '{"method": "ngram", "num_speculative_tokens": 20, "prompt_lookup_min": 2, "prompt_lookup_max": 5}'
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