RoBERTa

Model ● Covered in 6 stories + Follow

RoBERTa is a pre-trained language model that has been used in recent research for various natural language processing tasks including sentiment analysis, disaster tweet classification, and question-answering. Recent coverage shows RoBERTa being evaluated against other models like Llama 2 and Mistral, optimized for inference acceleration through ONNX Runtime quantization, and integrated into Graphcore's IPU-optimized transformer lineup, while also serving as a baseline for comparing efficiency gains from few-shot learning frameworks.

Updated 4 August 2026

Specifications

No specifications recorded yet.

Latest developments

Synthetic data: save money, time and carbon with open source Hugging Face · 2 years ago · 40

Comparing the Performance of LLMs: A Deep Dive into Roberta, Llama 2, and Mistral for Disaster Tweets Analysis with Lora Hugging Face · 2 years ago · 39

SetFit: Efficient Few-Shot Learning Without Prompts Hugging Face · 3 years ago · 9

Graphcore and Hugging Face Launch New Lineup of IPU-Ready Transformers Hugging Face · 4 years ago · 2

Accelerated Inference with Optimum and Transformers Pipelines Hugging Face · 4 years ago · 29

Generalized Language Models Lil'Log · 7 years ago · 23

Timeline

Month Quarter Year

2024

16 Feb Synthetic data: save money, time and carbon with open source

2023

7 Nov Comparing the Performance of LLMs: A Deep Dive into Roberta, Llama 2, and Mistral for Disaster Tweets Analysis with Lora

2022

2019

31 Jan Generalized Language Models

Relationships

Competition

SetFit competes with this model · 1 source

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