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Update README.md
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digicosmos86 authored Sep 19, 2024
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![PyPI - Downloads](https://img.shields.io/pypi/dm/HSSM?link=https%3A%2F%2Fpypi.org%2Fproject%2Fhssm%2F)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/hssm)
![GitHub pull requests](https://img.shields.io/github/issues-pr/lnccbrown/HSSM)
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![GitHub Repo stars](https://img.shields.io/github/stars/lnccbrown/HSSM)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

### Overview

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HSSM can be directly installed into your conda environment on Linux and MacOS. Installing HSSM on windows takes only one more simple step. We have a more detailed [installation guide](https://lnccbrown.github.io/HSSM/getting_started/installation/) for users with more specific setups.

**Important Update:** From HSSM 0.2.2, the official recommended way to install HSSM is through conda.

### Install HSSM on Linux and MacOS (CPU only)

Use the following command to install HSSM into your virtual environment:
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### Install HSSM on Windows (CPU only)

Because `jaxlib` is not available through `conda-forge` on Windows, you need to install JAX on Windows through `pip` before getting HSSM:
Because dependencies such as `jaxlib` and `numpyro` are not up-to-date on Conda, the easiest way to install HSSM on Windows is to install PyMC first and install HSSM via `pip`:

```bash
pip install jax
conda install -c conda-forge hssm
conda install -c conda-forge pymc
pip install hssm
```

### Install HSSM on Windows (with GPU support)

You simply need to install JAX with GPU support before getting HSSM:
You simply need to install JAX with GPU support after installing PyMC:

```bash
pip install jax[cuda12]
conda install -c conda-forge hssm
conda install -c conda-forge pymc
pip install hssm[cuda12]
```

### Support for Apple Silicon, AMD, and other GPUs
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