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 [TensorFlow Hub](https://tfhub.dev/tensorflow/bert_en_uncased_L-12_H-768_A-12/2). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment...
Model Package - Fulfilled on Amazon SageMaker
Explainable AI - NLP Models solution can identify the important words (tokens) from a text classification model and provide the effect they have on each predicted class. The solution can work with many sklearn based models without specifying the type of algorithm used to create these models. This...
Model Package - Fulfilled on Amazon SageMaker
This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/distilbert-base-multilingual-cased). 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 [TensorFlow Hub](https://tfhub.dev/tensorflow/bert_en_uncased_L-24_H-1024_A-16/2). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment...
Model Package - Fulfilled on Amazon SageMaker
Legal taxonomy classification is an important "first step" needed in legal text processing. You need to know what category of Law the legal text is referring to. Many Lawyers rely on the Legal Taxonomy provided by the LexisNexis application. This Sagemaker model isolates that taxonomy...
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 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
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