RoBERTa Programming Tutorials & Engineering Articles

The article discusses the implementation of LLM-powered relevance assessment at Pinterest Search, focusing on how fine-tuned large language models (LLMs) can enhance search relevance measurement wh...

The article discusses the implementation of a Large Language Model (LLM)-based relevance system for Pinterest Search, detailing its technical design, model architecture, and the results from both o...

The article discusses DragonCrawl, a generative AI system developed by Uber to enhance mobile testing by mimicking human-like interactions with applications.

The article discusses how to efficiently scale large language model (LLM) training across a large GPU cluster using the open-source frameworks Alpa and Ray.

This article discusses the deployment of NVIDIA TensorRT for AI inference on NVIDIA hardware, focusing on optimizing performance and compatibility.

This article discusses how Airbnb utilizes task-oriented conversational AI to enhance customer support for hosts and guests.

This article discusses how to leverage RAPIDS, HuggingFace, and Dask to run state-of-the-art NLP workloads at scale on GPUs.

The article discusses Image GPT, a generative model that applies the transformer architecture used in language models to image generation.

This article discusses the advancements in language modeling using Megatron on the NVIDIA A100 GPU, highlighting the significant improvements in natural language processing tasks achieved through m...

The Allen Institute for Artificial Intelligence has achieved a significant milestone with its BERT-based model, Aristo, which successfully passed a 12th-grade science exam with an accuracy of 83%.

NVIDIA has achieved a groundbreaking milestone by training BERT-Large in just 47 minutes using the DGX SuperPOD, and has also developed the largest Transformer-based model, GPT-2 8B, with 8.

The article discusses the optimizations NVIDIA has made to the BERT model using TensorRT, enabling real-time natural language understanding with significantly reduced latency.