torch-kitsune is an open-source Python package that predicts peak GPU memory usage, optimal batch size, and cost-effective GPU selection for PyTorch models. It helps machine learning engineers optimize model deployment and avoid out-of-memory errors.
torch-kitsune is a LLM eval & observability product. It focuses on predicting GPU memory requirements and optimal batch sizes for PyTorch model deployment. torch-kitsune is an open-source project aimed at machine learning engineers. The project is open source (MIT). It runs on the web and the command line, and it can be self-hosted.
torch-kitsune first shipped in 2025. Across PulseGate's embedding index, torch-kitsune has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are GPU memory prediction, batch size estimation, and pyTorch integration.
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