Captum
What is Captum?
Captum is a PyTorch library for model interpretability. It provides tools and techniques to understand and attribute the predictions of PyTorch models across various modalities, including vision and text. Captum supports most PyTorch models and allows for easy implementation and benchmarking of new interpretability algorithms.
How to use Captum?
Install Captum via conda or pip. Import necessary libraries like numpy, torch, and IntegratedGradients from captum.attr. Define and prepare your PyTorch model. Instantiate an interpretability algorithm (e.g., IntegratedGradients). Apply the algorithm to your input data and baseline to obtain attributions and convergence delta.
Captum's Core Features
Multi-modal interpretability support
Built on PyTorch
Extensible and open source
Captum's Use Cases
Understanding feature importance in image classification models
Analyzing the influence of words in text classification models
FAQ from Captum
How do I install Captum?
What types of models does Captum support?
What is Integrated Gradients?
Captum Company
Captum Company name: Facebook Inc. .
Captum Facebook
Captum Facebook Link: https://opensource.facebook.com/
Captum Github
Captum Github Link: https://github.com/pytorch/captum
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