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Requisitos previos y recomendaciones del sistema
Se requiere Python 3.11 o 3.12 para usar Meridian.
También recomendamos usar, al menos, 1 GPU.
Instalación
Para instalar Meridian, ejecuta el siguiente comando, que instala automáticamente la versión publicada más reciente de PyPI.
Linux (GPU)
python3-mpipinstall--upgrade'google-meridian[and-cuda]'# Verify the installation:python3-c"import meridian; print(meridian.__version__)"
macOS
python3-mpipinstall--upgrade'google-meridian'# Verify the installation:python3-c"import meridian; print(meridian.__version__)"
CPU
python3-mpipinstall--upgrade'google-meridian'# Verify the installation:python3-c"import meridian; print(meridian.__version__)"
Más reciente
python3-mpipinstall--upgradegit+https://github.com/google/meridian.git
# Verify the installation:python3-c"import meridian; print(meridian.__version__)"
Cómo usar la biblioteca de Meridian
Puedes ejecutar el código de Meridian de forma programática con datos de muestra por medio del Colab para principiantes.
El modelo Meridian usa un enfoque de muestreo de MCMC integral llamado No U Turn Sampler (NUTS), que puede requerir procesamiento intensivo. Para ayudar con esto, se desarrolló la compatibilidad con GPU en toda la biblioteca (lista para usar) con tensores. Te recomendamos ejecutar tu modelo Meridian en GPU para obtener resultados de optimización en tiempo real y reducir significativamente el tiempo de entrenamiento.
[null,null,["Última actualización: 2025-07-29 (UTC)"],[[["\u003cp\u003eMeridian requires Python 3.11 or 3.12 to operate.\u003c/p\u003e\n"],["\u003cp\u003eIt is recommended to use at least 1 GPU for optimal performance, with testing performed on V100 and T4 GPUs with 16 GB of RAM.\u003c/p\u003e\n"],["\u003cp\u003eMeridian can be installed using the command: \u003ccode\u003epip install --upgrade google-meridian\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eMeridian utilizes a compute-intensive No U Turn Sampler (NUTS) approach, and leveraging GPUs is advised to speed up optimization and reduce training times.\u003c/p\u003e\n"]]],["Meridian requires Python 3.11 or 3.12 and recommends at least 1 GPU (V100 or T4 with 16GB RAM tested). Installation via `pip` uses: `python3 -m pip install --upgrade 'google-meridian[and-cuda]'` (Linux/GPU), `google-meridian` (macOS/CPU). CPU-only install also uses `google-meridian`. To verify the install, run: `python3 -c \"import meridian; print(meridian.__version__)\"`. The library, which uses No U-Turn Sampler, is compute-intensive, thus GPU usage is recommended for real-time optimization and faster training.\n"],null,["# Install Meridian\n\nPrerequisites and system recommendations\n----------------------------------------\n\nPython 3.11 or 3.12 is required to use Meridian.\n\nWe also recommend using a minimum of 1 GPU.\n| **Note:** This project has been tested on V100 and T4 GPU using 16 GB of RAM.\n\nInstall\n-------\n\nTo install Meridian, run the following command to automatically install the most\nrecent published version from PyPI. \n\n### Linux (GPU)\n\n**Note:** CUDA toolchain and a compatible GPU device is necessary for `[and-cuda]` extra to activate. For CPU-only environment, see: \"CPU\". \n\n python3 -m pip install --upgrade 'google-meridian[and-cuda]'\n # Verify the installation:\n python3 -c \"import meridian; print(meridian.__version__)\"\n\n### macOS\n\n**Note:** There is no official GPU support for macOS. \n\n python3 -m pip install --upgrade 'google-meridian'\n # Verify the installation:\n python3 -c \"import meridian; print(meridian.__version__)\"\n\n### CPU\n\n python3 -m pip install --upgrade 'google-meridian'\n # Verify the installation:\n python3 -c \"import meridian; print(meridian.__version__)\"\n\n### Latest\n\n python3 -m pip install --upgrade git+https://github.com/google/meridian.git\n # Verify the installation:\n python3 -c \"import meridian; print(meridian.__version__)\"\n\nHow to use the Meridian library\n-------------------------------\n\nYou can run the Meridian code programmatically using sample data with\nthe [Getting started colab](/meridian/notebook/meridian-getting-started).\n\nThe Meridian model uses a holistic MCMC sampling approach called\n[No U Turn Sampler (NUTS)](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/mcmc/NoUTurnSampler)\nwhich can be compute intensive. To help with this, GPU support has been\ndeveloped across the library (out-of-the-box) using tensors. We recommend\nrunning your Meridian model on GPUs to get real time optimization results and\nsignificantly reduce training time."]]
