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  - OpenthaiGPT-13b
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  - LLMModel
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- # Large Language Model (LLM) README
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- ## Overview
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- This repository contains the implementation and resources for a Large Language Model (LLM) based on [OpenAI's GPT](https://openai.com/gpt) architecture. The model is trained on a diverse corpus of text data and can generate human-like text given a prompt.
 
 
 
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  ## Features
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- - **Text Generation**: The LLM can generate coherent and contextually relevant text given a prompt.
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- - **Fine-tuning**: This repository provides scripts and resources for fine-tuning the model on specific tasks or domains.
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- - **API Integration**: Instructions and resources for integrating the LLM into applications through APIs.
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- ## Installation
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- To use the LLM, follow these steps:
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- 1. Clone this repository: `git clone [repository-url]`
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- 2. Install the required dependencies: `pip install -r requirements.txt`
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- 3. Download the pre-trained model weights from [link] and place them in the `models` directory.
 
 
 
 
 
 
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- ## Usage
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- ### Generating Text
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- To generate text using the pre-trained model, run:
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  library_name: adapter-transformers
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  ---
 
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  - OpenthaiGPT-13b
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  - LLMModel
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+ # KIDDEE STRONG MUSCLE LLM
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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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+
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+ ## Introduction
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+
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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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  ## Features
 
 
 
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+ - **RAG architecture**: Integration of retrieval and generation models.
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+ - **LLM**: Powerful language generation capabilities.
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+ - **Question Answering**: Ability to answer questions based on given contexts.
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+ - **Scalable**: Easily scalable for large datasets and complex questions.
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+ - **Diverse Responses**: Provides diverse responses for a given question through generation.
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+
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+ ## Setup
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+
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+ 1. Clone this repository:
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+
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+ # I'm not going to tell you
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+ # sponser
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/652f721d7a8c08f81e6edfa3/hV0cTKic_YsySNYVrj9b0.png)
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  library_name: adapter-transformers
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  ---