An Open Source Machine Learning Framework for Everyone

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Graph Neural Network Library for PyTorch

Github Pages template based upon HTML and Markdown for personal, portfolio-based websites.

Open Source Neural Machine Translation and (Large) Language Models in PyTorch

Java 1-21 Parser and Abstract Syntax Tree for Java with advanced analysis functionalities.

[ICLR'24 spotlight] An open platform for training, serving, and evaluating large language model for tool learning.

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced research…

Numbers every LLM developer should know

Code for the paper "Evaluating Large Language Models Trained on Code"

Lingvo

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entr…

Guide to using pre-trained large language models of source code

Deep learning with dynamic computation graphs in TensorFlow

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

Code repo for "WebArena: A Realistic Web Environment for Building Autonomous Agents"

TensorFlow code for the neural network presented in the paper: "code2vec: Learning Distributed Representations of Code"

Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"

TensorFlow implementations of Graph Neural Networks

Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch

Code for the model presented in the paper: "code2seq: Generating Sequences from Structured Representations of Code"

PaL: Program-Aided Language Models (ICML 2023)

Machine Learning to Deobfuscate Binaries

Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020

A PyTorch Graph Neural Network Library

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

TensorFlow implementation of 'Attention Is All You Need (2017. 6)'