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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/distilroberta-base). 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 Natural Language Processing (NLP) based text classification solution that helps identify whether a given consumer complaint requires monetary compensation based on the complaint narrative. A complaint is classified as either requiring monetary relief or can be resolved through...
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/wiki_books/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...
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-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
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Text Classification API can help identify tags for a given body of text to classify it under different categories like business, sports, entertainment, politics, etc. The API gives percentage scores for different classification categories for a given input text. This API can be leveraged in use...
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
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