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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.

BERT 52
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Churn prediction using multimodality of text and tabular features with Amazon SageMaker Jumpstart

AWS Machine Learning Blog

In addition to textual inputs, this model uses traditional structured data inputs such as numerical and categorical fields. We show you how to train, deploy and use a churn prediction model that has processed numerical, categorical, and textual features to make its prediction. BERT + Random Forest.

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Top 6 NLP Language Models Transforming AI In 2023

Topbots

We’ll start with a seminal BERT model from 2018 and finish with this year’s latest breakthroughs like LLaMA by Meta AI and GPT-4 by OpenAI. BERT by Google Summary In 2018, the Google AI team introduced a new cutting-edge model for Natural Language Processing (NLP) – BERT , or B idirectional E ncoder R epresentations from T ransformers.

NLP 98
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MARKLLM: An Open-Source Toolkit for LLM Watermarking

Unite.AI

The KGW Family modifies the logits produced by the LLM to create watermarked output by categorizing the vocabulary into a green list and a red list based on the preceding token. Additionally, MARKLLM provides two types of automated demo pipelines, whose modules can be customized and assembled flexibly, allowing for easy configuration and use.

LLM 130
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How good is ChatGPT on QA tasks?

Artificial Corner

The DeepPavlov Library uses BERT base models to deal with Question Answering, such as RoBERTa. BERT is a pre-trained transformer-based deep learning model for natural language processing that achieved state-of-the-art results across a wide array of natural language processing tasks when this model was proposed.

ChatGPT 105
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TensorFlow Lite – Real-Time Computer Vision on Edge Devices (2024)

Viso.ai

Viso Suite is the End-to-End, No-Code Computer Vision Solution – Request a Demo. Text Classification: Categorize text into predefined groups for content moderation and tone detection. Natural Language Question Answering : Use BERT to answer questions based on text passages. What is Tensorflow Lite?

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Accelerating predictive task time to value with generative AI

Snorkel AI

Its categorical power is brittle. BERT for misinformation. Researchers using a BERT derivative—a non-generative LLM— achieved 91% accuracy in predicting COVID misinformation. The largest version of BERT contains 340 million parameters. Book a demo today. After this training, the model achieved an accuracy of 78%.