This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/distilbert-base-uncased). 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...
Model Package - Fulfilled on Amazon SageMaker
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
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
This is a Text Classification model built upon a Text Embedding model from [TensorFlow Hub](https://tfhub.dev/google/experts/bert/pubmed/1). It takes a text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model which is pre-trained on...
Model Package - Fulfilled on Amazon SageMaker
This solution classifies financial news headlines into positive, negative and neutral sentiments. It uses text analysis, natural language processing, machine learning techniques to predict the sentiment classes. This solution is built around specialized vocabulary encountered in finance and...
Model Package - Fulfilled on Amazon SageMaker
Amazon Textract is AWS' pay-as-you go OCR that uses artificial intelligence to automatically extract printed and handwritten text and retrieve data from scanned documents. Amazon Textract does not require preliminary configuration or training but apser's team can enhance the default output through...
This is a demo product from Amazon that showcases the Marketplace experience. It was created using this sample notebook https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb. Decision Trees (DTs) are a...
Model Package - Fulfilled on Amazon SageMaker
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
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Jina Embeddings v2 Small model is optimized for speed of inference and memory efficiency - For higher accuracy, use the Base model. jina-embeddings-v2-small-en is an open-source English embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many...
Model Package - Fulfilled on Amazon SageMaker
This solution provides an AutoML piepline which takes in an input csv that contains the labelled text data for any usecase along with a JSON file that contains the desired preprocessing steps that need to be used on the text data. The preprocessed data is then vectorized using different embeddings....
Model Package - Fulfilled on Amazon SageMaker
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