#自然语言处理#Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
#自然语言处理#Interpretability for sequence generation models 🐛 🔍
#自然语言处理#Collection of NLP model explanations and accompanying analysis tools
XAI Tutorial for the Explainable AI track in the ALPS winter school 2021
Overview of different model interpretability libraries.
#自然语言处理#A small repository to test Captum Explainable AI with a trained Flair transformers-based text classifier.
#自然语言处理#Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).
Cyber Security AI Dashboard
#自然语言处理#End-to-end toxic Russian comment classification
#计算机科学#This repository contains the source code for Indoor Scene Detector, a full stack deep learning computer vision application.
Interpretable graph classifications using Graph Convolutional Neural Network
#自然语言处理#Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously clas...
Model interpretability for Explainable Artificial Intelligence
#计算机科学#OdoriFy is an open-source tool with multiple prediction engines. This is the source code of the webserver.
This in an introduction to PyTorch Geometric, the deep learning library for Graph Neural Networks, and to interpretability tools for analyzing the decision process of a GNN.
#自然语言处理#Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_cl...
#计算机科学#PyTorch Beginner Workshop (Brad Heintz)