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| ## license: apache-2.0 | |
|  | |
| ## Datasets: | |
| - AIAT/Kiddee-data1234 | |
| - https://huggingface.co/AIAT/Kiddee-data1234 | |
| ## language: | |
| - th | |
| - en | |
| ## metrics: | |
| - accuracy 0.53 | |
| - response time 2.440 | |
| ## pipeline_tag: | |
| - table-question-answering | |
| ## tags: | |
| - OpenthaiGPT-13b | |
| - LLMModel | |
| # KIDDEE STRONG MUSCLE LLM | |
| This repository contains code and resources for building a Question Answering (QA) system using the Retrieval-Augmented Generation (RAG) approach with the Language Learning Model (LLM). | |
| ## Introduction | |
| RAG-QA combines the power of retrieval-based models with generative models to provide accurate and diverse answers to a given question. LLM, a state-of-the-art language model, is used for generation within the RAG framework. | |
| ## Features | |
| - **RAG architecture**: Integration of retrieval and generation models. | |
| - **LLM**: Powerful language generation capabilities. | |
| - **Question Answering**: Ability to answer questions based on given contexts. | |
| - **Scalable**: Easily scalable for large datasets and complex questions. | |
| - **Diverse Responses**: Provides diverse responses for a given question through generation. | |
| ## Setup | |
| 1. Clone this repository: | |
| # I'm not going to tell you | |
| # sponser | |
|  | |
| library_name: adapter-transformers | |
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