This repository collects all relevant resources about interpretability in LLMs

Implementation of the stacked denoising autoencoder in Tensorflow

Pytorch implementations of various types of autoencoders

Evaluate interpretability methods on localizing and disentangling concepts in LLMs.

Tensorflow Examples

Experiments with Adversarial Autoencoders using Keras

Sparse Auto Encoder and regular MNIST classification with mini batch's

Repository of Deep Propensity Network - Sparse Autoencoder(DPN-SA) to calculate propensity score using sparse autoencoder

Multi-Layer Sparse Autoencoders

Providing the answer to "How to do patching on all available SAEs on GPT-2?". It is an official repository of the implementation of the paper "Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small"

Collection of autoencoder models in Tensorflow

Explore visualization tools for understanding Transformer-based large language models (LLMs)

Implemented semi-supervised learning for digit recognition using Sparse Autoencoder

A resource repository of sparse autoencoders for large language models

exploration WYSIWYG editor

Neural Network Architcture | ISI Kolkata

This repository contains Python codes for Autoenncoder, Sparse-autoencoder, HMM, Expectation-Maximization, Sum-product Algorithm, ANN, Disparity map, PCA.

Interpret and control dense embedding via sparse autoencoder.

Sparse Autoencoder based on the Unsupervised Feature Learning and Deep Learning tutorial from the Stanford University

Folder contains implementation of Multi layer feed forward networks, Autoencoders, Sparse Autoencoders and many..