Some benchmarks for evaluating different models with a small dataset, within Databricks MLR notebook: Model2.18.02.19.0rc0This PR Scikit-learn + OSS eval (code) 10.71 sec 15.11 sec 10.86 sec LangChain + DB Agent eval (*1) 13.63 sec 18.70 sec 14.66 sec (*1) Langchain eval time heavily...
These are not rigorous or scientific benchmarks, but they’re intended to give you a quick overview of how the tools overlap and how they differ from each other. For more details, see the head-to-head comparison below. Airflow, MLflow or Kubeflow for MLOps? https://www.vietanh.dev/bl...
It is a good strategy to perform LLM latency/throughput benchmarking before deploying the model in earnest. Benchmark the following metrics as a baseline. metrics = { 'threads': num_threads, 'duration': duration, 'throughput': throughput, 'avg_sec': avg_latency, '...