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A lightweight and efficient English to Tamil translation model implementation using Google's Gemma 2b. This project aims to bridge language barriers while maintaining cultural nuances and context.
A RAG (Retrieval-Augmented Generation) application combines large language models (LLMs) with a retrieval system to enhance the generation of responses by accessing relevant external knowledge. In this specific case, the RAG application is developed using the GROQ API, OpenAI embeddings, and is trained on the Gemma model.
This app is built to simplify the task of summarizing textual content from YouTube videos and websites. By integrating LangChain with the Groq API for natural language processing (NLP), it delivers concise and efficient summaries from a variety of content sources.
Automate metadata extraction for Parquet & ORC datasets (schema, outliers, contextual, skewness, semanto) with this toolkit. Compatible with Google Gemma and Meta Llama frameworks.
Neuron is a conversational AI model using the Gemma LLM by Google from Hugging Face. It is designed to engage in a variety of topics and provide information on a wide range of subjects. With its ability to learn and adapt, this chatbot can provide a unique and engaging experience.