AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
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Updated
Sep 9, 2024 - TypeScript
AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs.
An LLM app leveraging RAG with LangChain and GPT-4 mini to analyze earnings call transcripts, assess company performance, using natural language queries (NLP), FAISS (vector database), and Hugging Face re-ranking models.
Factoid Question Answering System - An advanced Open-domain Question Answering (ODQA) project that automatically answers factoid questions in Arabic and English languages using NLP and machine learning techniques
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It is a Mental Health Chatbot named CogniCare. Whether you're feeling overwhelmed, anxious, or just need someone to talk to, our Mental Health Chatbot is here to support you every step of the way. Remember, it's okay to seek help, and you don't have to go through this alone.
It is an innovative repository housing a sophisticated Large Language Model (LLM) project, showcasing the intersection of advanced natural language processing and cutting-edge artificial intelligence. This repository serves as a comprehensive platform for the development, experimentation, and application of state-of-the-art language models.
Sistem Tanya Jawab menggunakan Metode N-Gram dan Vector Space Model
This repository contains a Streamlit-based Document Question Answering System implementing the Retrieve-and-Generate (RAG) architecture, utilizing Streamlit for the UI, LangChain for text processing, and Google Generative AI for embeddings.
System uses Google Gemini which takes PDF and we have to ask question based on the context of that PDF. System will provide the answer of the question.
A Turkish question answering system made by fine-tuning BERTurk and XLM-Roberta models.
A Turkish question answering system made by fine-tuning BERTurk and XLM-Roberta models.
Comparative study of large language models in the field of open-book QA, with application to a real-life use case.
Machine Comprehension on Squad Dataset using Match-LSTM + Ans-Ptr Network
Question Answering dataset generator of Document Visual in English and Chinese
A enhanced Open Dialogue Context Generator supported by General Language Model Pretraining with Autoregressive Blank Infilling
A Daliy Dialogue Context Generator trained with Bloom and GPT
Successfully leveraged a pretrained BERT Transformer model for developing a question answering system.
Development of a question answering system for the university software Agnes.
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