647 Open source projects that are alternatives of or similar to Transformer-MM-Explainability

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

Collection of NLP model explanations and accompanying analysis tools

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Fit interpretable models. Explain blackbox machine learning.

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A library for finding knowledge neurons in pretrained transformer models.

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XAI Tutorial for the Explainable AI track in the ALPS winter school 2021

Trained T5 and T5-large model for creating keywords from text

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

For calculating global feature importance using Shapley values.

Handwritten text recognition using transformers.

Summary of Transformer applications for computer vision tasks.

Molecular Explanation Generator

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

A lightweight implementation of removal-based explanations for ML models.

State-of-the-art NLP through transformer models in a modular design and consistent APIs.

HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

Code for NeurIPS 2019 paper ``Self-Critical Reasoning for Robust Visual Question Answering''

Papers about explainability of GNNs

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Adaptive, interpretable wavelets across domains (NeurIPS 2021)

Data generator for Arena - interactive XAI dashboard

Examples of Data Science projects and Artificial Intelligence use cases

Implementation of the paper Video Action Transformer Network

Variational Transformers for Diverse Response Generation

莱斯杯：全国第二届“军事智能机器阅读”挑战赛 - Rank7 解决方案

Code for Editing Factual Knowledge in Language Models

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Pytorch implementation of "All Tokens Matter: Token Labeling for Training Better Vision Transformers"

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

Using Transformers from HuggingFace in R

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data

Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks, debuted in ICLR 2022

A simple Neural Network for sentiment analysis, embedding sentences using a Transformer network.

A more handy way to use SPARQL data in your web app

SImple SenTence EmbeddeR

This repo provides the official code for : 1) TransBTS: Multimodal Brain Tumor Segmentation Using Transformer (https://arxiv.org/abs/2103.04430) , accepted by MICCAI2021. 2) TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images(https://arxiv.org/abs/2201.12785).

Text Simplification Model based on Encoder-Decoder (includes Transformer and Seq2Seq) model.

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

AI to Combat Environmental Pollution - detecting plastic waste in the environment to combat environmental pollution and promote circular economy (Deep Learning, PyTorch)

A middleware to switch fractal serializers in dingo

Continuous Augmented Positional Embeddings (CAPE) implementation for PyTorch

ExpMRC: Explainability Evaluation for Machine Reading Comprehension

Transformer/Transformer-XL/R-Transformer examples and explanations

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A Pytorch implementation of CVPR 2020 paper: Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text

ALPR model in unconstrained scenarios for Chinese license plates

A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.

Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention

Leetcode using AI