TorchDrift VS Transformer-MM-Explainability

Compare TorchDrift vs Transformer-MM-Explainability and see what are their differences.

TorchDrift

Drift Detection for your PyTorch Models (by TorchDrift)
drift-detection Pytorch neural-networks AI
Source Code
torchdrift.org
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Transformer-MM-Explainability

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA. (by hila-chefer)
Transformers Transformer vqa detr Visualization explainability explainable-ai Interpretability lxmert visualbert clip
Source Code
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TorchDrift Transformer-MM-Explainability
1 3
302 704
0.0% -
0.0 0.0
over 1 year ago 8 months ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

TorchDrift

Posts with mentions or reviews of TorchDrift. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

Transformer-MM-Explainability

Posts with mentions or reviews of Transformer-MM-Explainability. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

When comparing TorchDrift and Transformer-MM-Explainability you can also consider the following projects:

cockpit - Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

explainerdashboard - Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

loss-landscape - Code for visualizing the loss landscape of neural nets

shap - A game theoretic approach to explain the output of any machine learning model.

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

pytea - PyTea: PyTorch Tensor shape error analyzer

WeightWatcher - The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

TorchDrift vs cockpit Transformer-MM-Explainability vs pytorch-grad-cam TorchDrift vs uncertainty-toolbox Transformer-MM-Explainability vs explainerdashboard TorchDrift vs loss-landscape Transformer-MM-Explainability vs shap TorchDrift vs cleverhans Transformer-MM-Explainability vs pytea TorchDrift vs WeightWatcher Transformer-MM-Explainability vs WeightWatcher TorchDrift vs explainerdashboard Transformer-MM-Explainability vs cleverhans