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
Active Learning for Text Classification trains a text classification model using a small corpus of training data and provides the most appropriate samples from a huge corpus of unlabeled data to be annotated in order to improve the model accuracy significantly. Using Active Learning this algorithm...
Algorithm - 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_wwm_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...
Model Package - Fulfilled on Amazon SageMaker
A high frequency of issues can generate an overwhelming number of service desk tickets and incorrect delegation to teams to handle them. This leads to a spike in MTTR (mean time taken to resolve) and a dip in FCR (First Call Resolution). The solution mitigates these issues by training a...
Algorithm - Fulfilled on Amazon SageMaker
This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/roberta-large). 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
This is a Text Classification model built upon a Text Embedding model from [TensorFlow Hub](https://tfhub.dev/tensorflow/bert_en_wwm_uncased_L-24_H-1024_A-16/2). It takes a text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model...
Model Package - Fulfilled on Amazon SageMaker
A high frequency of issues can generate an overwhelming number of tickets and incorrect delegation to teams to handle them. This leads to a spike in MTTR (mean time taken to resolve) and a dip in FCR (First Call Resolution). The solution mitigates these issues by training a multi-factor ML model...
Algorithm - Fulfilled on Amazon SageMaker
This is a Text 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 text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model which is...
Model Package - Fulfilled on Amazon SageMaker
This solution identifies the various aspects a reviewer is mentioning when providing a review for any restaurant business. This can help businesses easily identify which are its most prominent aspects (e.g. price, ambience, taste, quality etc.) which are getting reviewed and what are the associated...
Model Package - Fulfilled on Amazon SageMaker
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jina-embeddings-v2-base-zh is an open-source bilingual Chinese-English embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many applications, such as document clustering, classification, content personalization, vector search, or retrieval augmented...
Model Package - Fulfilled on Amazon SageMaker
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