Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
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lm-evaluation-harness evaluates LLMs across 60+ academic benchmarks using standardized prompts and metrics.
Installation:
pip install lm-evalEvaluate any HuggingFace model:
lm_eval --model hf \
--model_args pretrained=meta-llama/Llama-2-7b-hf \
--tasks mmlu,gsm8k,hellaswag \
--device cuda:0 \
--batch_size 8View available tasks:
lm_eval --tasks list[Description truncada. Veja o README completo no GitHub.]