Remove 12 dependency-parsing-in-natural-language-processing-with-examples
article thumbnail

ML and NLP Research Highlights of 2021

Sebastian Ruder

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP).   2021 saw the continuation of the development of ever larger pre-trained models. In vision and language, controlled studies shed new light on important components of such multi-modal models [11] [12].

NLP 52
article thumbnail

Creating your own code writing agent. How to get results fast and avoid the most common pitfalls

deepsense.ai

In this blog post we walk you through our journey creating an LLM-based code writing agent from scratch – fine tuned-for your needs and processes – and we share our experience of how to improve it iteratively. Introduction This article is the second part in our series on Coding Agents. We utilized the GPT-3.5

LLM 113
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

article thumbnail

Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

LLM 52