research
∙
04/21/2023
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
It is widely acknowledged that large models have the potential to delive...
share
research
∙
05/02/2022
OPT: Open Pre-trained Transformer Language Models
Large language models, which are often trained for hundreds of thousands...
research
∙
03/14/2022
Efficient Language Modeling with Sparse all-MLP
All-MLP architectures have attracted increasing interest as an alternati...
research
∙
12/20/2021
Efficient Large Scale Language Modeling with Mixtures of Experts
Mixture of Experts layers (MoEs) enable efficient scaling of language mo...
research
∙
12/20/2021
Few-shot Learning with Multilingual Language Models
Large-scale autoregressive language models such as GPT-3 are few-shot le...
research
∙
10/18/2021
NormFormer: Improved Transformer Pretraining with Extra Normalization
During pretraining, the Pre-LayerNorm transformer suffers from a gradien...
research
∙
10/06/2021
8-bit Optimizers via Block-wise Quantization
Stateful optimizers maintain gradient statistics over time, e.g., the ex...
research
∙
10/24/2020
Pre-trained Summarization Distillation
Recent state-of-the-art approaches to summarization utilize large pre-tr...
research
∙
12/11/2019
Incrementally Improving Graph WaveNet Performance on Traffic Prediction
We present a series of modifications which improve upon Graph WaveNet's ...
research
∙
11/16/2019
Classification as Decoder: Trading Flexibility for Control in Medical Dialogue
Generative seq2seq dialogue systems are trained to predict the next word...
research
∙
10/04/2019
Classification As Decoder: Trading Flexibility For Control In Neural Dialogue
Generative seq2seq dialogue systems are trained to predict the next word...
research
∙
06/12/2019
Using Small Proxy Datasets to Accelerate Hyperparameter Search
One of the biggest bottlenecks in a machine learning workflow is waiting...
research
∙
03/21/2019
