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• Version 5.2.8
• By John Snow Labs

This model specializes in identifying key risk factors such as Coronary Artery Disease, Diabetes, Family History, Hyperlipidemia, Hypertension, Medications, Obesity, and Smoking Habits in clinical documentation. Designed for precision, it assists healthcare professionals in crucial risk assessment...

Model Package - Fulfilled on Amazon SageMaker

• Version 1.2
• By Mphasis

This solution identifies the various aspects from online product reviews for screen guards. The following 7 aspects are identified: transparency, protection, adhesive, surface, fit and, price. This enables companies to easily identify which aspects are being reviewed. This information can be used...

Model Package - Fulfilled on Amazon SageMaker

• Version GPU
• By Amazon Web Services

This is a Sentence Pair Classification model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies...

Model Package - Fulfilled on Amazon SageMaker

• By Spectrum Labs

Guardian uses true Natural Language Understanding (NLU) AI to go beyond keyword-based filters to detect harmful or healthy content. Guardian can discover and act at scale on difficult-to-detect behaviors that other solutions miss: Child sexual abuse material (CSAM) Bullying Hate...

• Version GPU
• By Amazon Web Services

This is a Text Summarization model built upon a Transformer model from [Hugging Face](https://huggingface.co/google/bigbird-pegasus-large-arxiv). The deployed model can be used for running inference on any English input text.

Model Package - Fulfilled on Amazon SageMaker

• Version 2.0
• By Mphasis

This solution identifies and anonymizes Personally Identifiable Information like Name, SSN, Email, Phone numbers from tabular data. The Solution is designed to work on structured data source.

Model Package - Fulfilled on Amazon SageMaker

• Version GPU
• By Amazon Web Services

This is a Sentence Pair Classification model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies...

Model Package - Fulfilled on Amazon SageMaker

• Version CPU
• By Amazon Web Services

This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/bert-base-cased). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence...

Model Package - Fulfilled on Amazon SageMaker

• By Celebal Technologies

Are you facing challenges in your call center operations? Challenges such as long call duration, inefficient query resolution, frequent escalations, and increased agent workload? Our Intelligent Contact Center Solution CT-CCI, powered by AWS Bedrock, addresses these challenges by incorporating...

• By BigData Boutique

To make the most out of search engine software like Elasticsearch, when dealing with Hebrew texts a dedicated conversion layer (Analyzer) has to be used in order for Hebrew to even be searchable, and to leverage the full range of features provided by the search engine itself. Eyfo's Hebrew Search...