A Personalized Assistant with Gemma 2b
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Updated
Mar 15, 2024 - Jupyter Notebook
A Personalized Assistant with Gemma 2b
AskPdf is a Streamlit-based application for question-answering over PDF documents using Retrieval-Augmented Generation (RAG) with conversational history. Upload your PDFs and interactively ask questions to get concise, contextually relevant answers, leveraging LangChain, Chroma for vector storage, and HuggingFace embeddings.
A Vision Language Model implemented in PyTorch
Google – AI Assistants for Data Tasks with Gemma
ML Bot is a RAG Application built using google/gemma-2b-it local LLM
This project demonstrates the steps required to fine-tune the Gemma model for tasks like code generation. We use qLora quantization to reduce memory usage and the SFTTrainer from the trl library for supervised fine-tuning.
GemmaLLM RAG chatbot
Tools and method for fine-tuning the Gemma 2 model on custom datasets
A Retrieval Augmented Generator (RAG) that operates entirely locally, combining document retrieval and language model generation to provide accurate and contextually relevant responses. Built with @langchain-ai
A langchain application that use open-source gemma2:2b LLM model.
Fine-tune the Gemma2B language model on a climate-related question-answer dataset to improve its domain-specific knowledge using LoRA (Low Rank Adaptation).
This project is an AI-powered chat interface developed using Next.js and Tailwind CSS. It allows users to interact with an artificial intelligence model similar to ChatGPT, generating responses based on user input. However, to utilize the AI model, you need access to the Ollama platform, which includes the Gemma:2b model.
Evaluation of Google's Instruction Tuned Gemma-2B, an open-source Large Language Model (LLM). Aimed at understanding the breadth of the model's knowledge, its reasoning capabilities, and adherence to ethical guardrails, this project presents a systematic assessment across a diverse array of domains.
EMSUGI is a future prediction & analysis project on various factor like flood, earth quake, disease occurred on your neighborhood location.
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