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Training Relations Models in NLP Lab 5.7

John Snow Labs

marks a significant milestone in the realm of natural language processing with the introduction of advanced Relation Extraction (RE) model training features. Efficient Model Management: Effortlessly download, upload, and publish trained RE models for collaborative use and broader community access through the Models Hub.

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Top Call Center QA Challenges & How To Overcome Them with AI

LevelAI

Limited options for auto-QA Many companies use automated QA (auto QA) services to monitor customer interactions. However, this is a relatively small market with limited solutions, and most auto-QA tools fail to deliver actionable results. Oftentimes, they fail to produce accurate or relevant results. Get a free demo today!

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Top Speech to Text AI Tools (2023)

Marktechpost

For computers to process, analyze, interpret, and reason about human language, a subfield of AI known as natural language processing (NLP) is required. Natural language processing (NLP) is an interdisciplinary field that draws on methods from disciplines as diverse as linguistics and computer science.

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How to Use Hugging Face Pipelines?

Towards AI

It allows you to easily download and train state-of-the-art pre-trained models. Next, when creating the classifier object, the model was downloaded. Our model gets a prompt and auto-completes it. Let’s go ahead and have a look at what the Transformers library is. What is the Transformers library? Let me explain.

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Unlocking creativity: How generative AI and Amazon SageMaker help businesses produce ad creatives for marketing campaigns with AWS

AWS Machine Learning Blog

SageMaker endpoints also have auto scaling features and are highly available. In the following code, we download the model weights for the different ControlNet techniques and Stable Diffusion 1.5 Flexibility – When creating and deploying endpoints, SageMaker provides the flexibility to choose GPU instance types.

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Text to Exam Generator (NLP) Using Machine Learning

Mlearning.ai

There will be a lot of tasks to complete. I came up with an idea of a Natural Language Processing (NLP) AI program that can generate exam questions and choices about Named Entity Recognition (who, what, where, when, why). Are you ready to explore? Let’s begin! The approach was proposed by Yin et al.

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Deploy a Hugging Face (PyAnnote) speaker diarization model on Amazon SageMaker as an asynchronous endpoint

AWS Machine Learning Blog

The added benefit of asynchronous inference is the cost savings by auto scaling the instance count to zero when there are no requests to process. SageMaker features and capabilities help developers and data scientists get started with natural language processing (NLP) on AWS with ease.