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Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning

AWS Machine Learning Blog

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. First, we use an Amazon SageMaker Studio notebook to fine-tune a pre-trained BERT model on a target task using a domain-specific dataset.

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Top Artificial Intelligence AI Courses from Google

Marktechpost

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. Transformer Models and BERT Model This course introduces the Transformer architecture and the BERT model, covering components like the self-attention mechanism.

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BERT models: Google’s NLP for the enterprise

Snorkel AI

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. Additionally, while the data and code needed to train some of the latest generation of models is still closed-source, open source variants of BERT abound.

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Modern NLP: A Detailed Overview. Part 3: BERT

Towards AI

In this article, we will talk about another and one of the most impactful works published by Google, BERT (Bi-directional Encoder Representation from Transformers) BERT undoubtedly brought some major improvements in the NLP domain. Architecture: The authors have used a two-layered Bidirectional LSTM to demo the concept.

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BERT models: Google’s NLP for the enterprise

Snorkel AI

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. Additionally, while the data and code needed to train some of the latest generation of models is still closed-source, open source variants of BERT abound.

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Legal NLP releases new LLM demos, LLM-based Question Answering, Longformer and Camembert models , Greek Regulation Classification and notebooks and demos

John Snow Labs

Question / Answering in Legal NLP using Flan-T5 LLM demos A new demo has been released showcasing how to use Flan-T5 models, finetuned on legal texts to carry out summarization , text generation and question answering. Demo available here. Let’s take a look at each of them!

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From Dev to Production: Deploying HuggingFace BERT with KServe

Mlearning.ai

The Future of NLP Deployment: BERT Models and KServe in Action In this post, I will demonstrate how to deploy a HuggingFace pre-trained model (BERT for text classification with the Hugging Face Transformers library) to run as a KServe-hosted model. First, let’s understand what is KServe and why we need KServe. ?What What is KServe?

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