llm_benchmark: AI Performance Measure AI model performance with llm_benchmark, used by founders with 1.4k+ GitHub stars, for informed decisions.
100% free ยท open source
llm_benchmark measures the performance of AI models, providing founders with actionable insights to inform their decisions.
git clone https://github.com/llm2014/llm_benchmark.git
โข When evaluating the accuracy of different AI models for a startup's applicationโข To compare the performance of various AI models on a specific datasetโข Before deploying an AI model to production, to ensure it meets performance requirements1 Navigate to the cloned repository: cd llm_benchmark 2 Install required packages: pip install -r requirements.txt 3 Prepare the dataset: python scripts/prepare_data.py --dataset_name [your_dataset_name] 4 Run the benchmark: python scripts/run_benchmark.py --model_name [your_model_name] --dataset_name [your_dataset_name] 5 View the results: python scripts/view_results.py --model_name [your_model_name] --dataset_name [your_dataset_name] Ready-to-paste prompt python scripts/run_benchmark.py --model_name bert-base-uncased --dataset_name sst-2 Heads up: The repository uses Python 3.8 or later, and some models may require specific dependencies or GPU acceleration, so ensure your environment meets these requirements before running the benchmark
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