Captum · Model Interpretability for PyTorch
Captum is an open-source, extensible library for model interpretability built on PyTorch, providing state-of-the-art algorithms to understand which features are contributing to a model’s output.
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https://captum.ai/
Product Information
Updated:07/04/2024
What is Captum · Model Interpretability for PyTorch
Captum is a comprehensive tool for model interpretability, designed to facilitate understanding of complex PyTorch models. It offers a wide range of algorithms and visualization tools to help researchers and developers identify the key features driving model predictions. Captum supports most types of PyTorch models and can be used with minimal modification to the original neural network.
Key Features of Captum · Model Interpretability for PyTorch
Captum provides a suite of algorithms and visualization tools for model interpretability.
Integrated Gradients: Calculates the importance of each feature by integrating the gradients of the output with respect to the input.
GradientShap: A feature attribution method that assigns importance scores to each feature based on the gradient of the output with respect to the input.
Occlusion: A perturbation-based algorithm that examines the changes in the output of a model in response to changes in the input.
Captum Insights: A visualization widget that provides ready-made visualizations for image, text, and arbitrary model types.
Pros
Supports most types of PyTorch models
Extensible and open-source
Provides a wide range of algorithms and visualization tools
Easy to use and integrate with existing models
Cons
May require significant computational resources for large models
Some algorithms can be computationally expensive
Use Cases of Captum · Model Interpretability for PyTorch
Computer vision
Natural language processing
Recommendation systems
Adversarial attacks and robustness
How to Use Captum · Model Interpretability for PyTorch
Install Captum using pip or conda
Import Captum in your Python script
Load your PyTorch model
Choose an attribution algorithm
Run the attribution algorithm on your model
Visualize the attribution results using Captum Insights
Captum · Model Interpretability for PyTorch FAQs
Captum is an open-source, extensible library for model interpretability built on PyTorch.
Analytics of Captum · Model Interpretability for PyTorch Website
Captum · Model Interpretability for PyTorch Traffic & Rankings
38.9K
Monthly Visits
#1540655
Global Rank
#19157
Category Rank
Traffic Trends: Mar 2024-May 2024
Captum · Model Interpretability for PyTorch User Insights
00:07:46
Avg. Visit Duration
1.54
Pages Per Visit
32.53%
User Bounce Rate
Top Regions of Captum · Model Interpretability for PyTorch
US: 12.23%
DE: 9.31%
NL: 8.06%
VN: 5.03%
PL: 3.71%
Others: 61.66%
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