llm_benchmark: AI Performance
llm_benchmark measures the performance of AI models, providing founders with actionable insights to inform their decisions.
- •When evaluating the accuracy of different AI models for a startup's application
- •To compare the performance of various AI models on a specific dataset
- •Before deploying an AI model to production, to ensure it meets performance requirements
python scripts/run_benchmark.py --model_name bert-base-uncased --dataset_name sst-2
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/llm-benchmark && curl -fsSL https://workflowstacks.com/api/skills/llm-benchmark/claude-skill -o ~/.claude/skills/llm-benchmark/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Llm_benchmark: AI Performance is a medium project (~3.9k lines across 4 code files). Expect some technical setup — comfortable with a terminal, or ask a developer. Last commit this month, no license file, no tests found.
- 1README.mdStart here — what it does and how to install it
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/llm-benchmark && curl -fsSL https://workflowstacks.com/api/skills/llm-benchmark/claude-skill -o ~/.claude/skills/llm-benchmark/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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