The Big 5 personality analyser takes input text from a user and assigns score on the Big 5 personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism). The underlying algorithm utilises Natural Language Processing and computational psycho-linguistics to assign the...
Model Package - Fulfilled on Amazon SageMaker
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jina-embeddings-v2-base-de is an open-source bilingual German-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
This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/bert-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
Cohere’s Classification Finetuning enables you to train and deploy classification models with a few lines of code. Using as few as 2 examples per label, users are able to train custom models to classify text based on semantic meaning (results will vary depending on the classification task at hand -...
Algorithm - Fulfilled on Amazon SageMaker
The Universal Sentence Encoder encodes text into high-dimensional vectors that can be used for text classification, semantic similarity, clustering and other natural language tasks. The model is trained and optimized for greater-than-word length text, such as sentences, phrases or short...
Model Package - Fulfilled on Amazon SageMaker
This solution classifies airline reviews into positive and negative sentiments. It uses text analysis, natural language processing, machine learning techniques to predict sentiment classes for airline reviews. It also generates two word clouds: one each for positive and negative sentiment reviews....
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_wwm_cased_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
A high frequency of issues can generate an overwhelming number of customer complaint 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 [TensorFlow Hub](https://tfhub.dev/tensorflow/bert_en_cased_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
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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