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--- |
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license: apache-2.0 |
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datasets: |
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- AIAT/Kiddee-data1234 |
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language: |
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- th |
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- en |
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metrics: |
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- accuracy |
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library_name: transformers |
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pipeline_tag: table-question-answering |
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tags: |
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- code |
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- openthaigpt |
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--- |
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--- |
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## license: apache-2.0 |
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## Tag |
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- openthaigpt/openthaigpt-1.0.0-13b-chat |
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## Datasets: |
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- (https://huggingface.co/datasets/AIAT/Kiddee-data1234) |
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## language: |
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- th |
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- en |
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## metrics: |
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- accuracy 0.53 |
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- response time 2.440 |
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## pipeline_tag: |
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- table-question-answering |
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## tags: |
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- OpenthaiGPT-13b |
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- LLMModel |
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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). |
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## Introduction |
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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. |
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# sponser |
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library_name: adapter-transformers |
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--- |