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<a href="https://nlp.stanford.edu/~wuzhengx/"><strong>Library Paper and Doc Are Forthcoming »</strong></a>
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</div>
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<a href="https://pypi.org/project/pyvene/"><img src="https://img.shields.io/pypi/v/pyvene?color=red"></img></a>
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# **pyvene: Use _Interventions_ to Learn Model's _Causal Mechanisms_**
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**pyvene** supports customizable interventions on different neural architectures (e.g., RNN or Transformers). It supports complex intervention schemas (e.g., parallel or serialized interventions) and a wide range of intervention modes (e.g., static or trained interventions) at scale to gain interpretability insights.
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**Getting Started:** [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/frankaging/pyvene/blob/main/tutorials/basic_tutorials/Basic_Intervention.ipynb) [**pyvene Intervention 101**]
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**Getting Started:** [<img align="center" src="https://colab.research.google.com/assets/colab-badge.svg" />](https://colab.research.google.com/github/frankaging/pyvene/blob/main/tutorials/basic_tutorials/Basic_Intervention.ipynb) [**_pyvene_ 101**]
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## Installation
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Install this package directly from the source code as,
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Install with pip on stable releases,
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```bash
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pip install pyvene
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```
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or with our dev repo directly,
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```bash
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!pip install git+https://github.com/frankaging/pyvene.git
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pip install git+https://github.com/frankaging/pyvene.git
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```
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## _Wrap_ , _Intervene_ and _Share_

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