Code Llama: Open Foundation Models for Code

2 code implementations • 24 Aug 2023 • Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, Gabriel Synnaeve

We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks.

16k Code Generation +1

AECMOS: A speech quality assessment metric for echo impairment

no code implementations • 6 Oct 2021 • Marju Purin, Sten Sootla, Mateja Sponza, Ando Saabas, Ross Cutler

Traditionally, the quality of acoustic echo cancellers is evaluated using intrusive speech quality assessment measures such as ERLE \cite{g168} and PESQ \cite{p862}, or by carrying out subjective laboratory tests.

Crowdsourcing approach for subjective evaluation of echo impairment

1 code implementation • 25 Oct 2020 • Ross Cutler, Babak Naderi, Markus Loide, Sten Sootla, Ando Saabas

The quality of acoustic echo cancellers (AECs) in real-time communication systems is typically evaluated using objective metrics like ERLE and PESQ, and less commonly with lab-based subjective tests like ITU-T Rec.

Non-Synergistic Variational Autoencoders

no code implementations • ICLR 2019 • Gonzalo Barrientos, Sten Sootla

Learning disentangling representations of the independent factors of variations that explain the data in an unsupervised setting is still a major challenge.

Disentanglement