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bayazitdeniz's starred repositories

LoRA-XS

LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Language:Python700

deeplearning-models

A collection of various deep learning architectures, models, and tips

Language:Jupyter NotebookMIT1639700

reckoning-metakg

RECKONING is a bi-level learning algorithm that improves language models' reasoning ability by folding contextual knowledge into parametric knowledge through back-propagation.

Language:PythonMIT300

NeuroSurgeon

NeuroSurgeon is a package that enables researchers to uncover and manipulate subnetworks within models in Huggingface Transformers

Language:PythonMIT3300

A neural-symbolic joint reasoning approach for Natural Language Inference (NLI). Modeling NLI as inference path planning through a search engine. Sequence chunking and neural paraphrase detection for syntactic variation. SOTA result on SICK and MED.

Language:Jupyter NotebookMIT1500

disco

Generating diverse counterfactual data for Natural Language Understanding tasks using Large Language Models (LLMs). The generator supports GPT-3, ChatGPT, and GPT-4.

Language:PythonMIT3200

epic-guide.github.io

Guidebook for IC PhD life at EPFL

Language:DockerfileNOASSERTION1300

genmos_object_search

GenMOS - A System for Generalized (off-the-shelf) 3D Multi-Object Search | ICRA 2023

Language:PythonMIT2000

affordance-language

Code for RSS 2020 paper: Robot Object Retrieval with Contextual Natural Language Queries

Language:Python1400

lm-debugger

The official code of LM-Debugger, an interactive tool for inspection and intervention in transformer-based language models.

Language:PythonApache-2.015800

thortils

Utility functions when working with Ai2-THOR. Try to do one thing once.

Language:PythonMIT3900

kogito

A Python Commonsense Knowledge Inference Toolkit

Language:PythonApache-2.05900

tmux

tmux source code

Language:CNOASSERTION3351000

matplotlib-venn

Area-weighted venn-diagrams for Python/matplotlib

Language:Jupyter NotebookMIT49200

modules

The official repository for our paper "Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks". We develop a method for analyzing emerging functional modularity in neural networks based on differentiable weight masks and use it to point out important issues in current-day neural networks.

Language:PythonBSD-3-Clause4500

rome

Locating and editing factual associations in GPT (NeurIPS 2022)

Language:PythonMIT51000

PyTorchZeroToAll

Simple PyTorch Tutorials Zero to ALL!

Language:Python385700

ff-layers

The accompanying code for "Transformer Feed-Forward Layers Are Key-Value Memories". Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. EMNLP, 2021.

Language:PythonMIT7200