EMSUGI is a future prediction & analysis project on various factor like flood, earth quake, disease occurred on your neighborhood location.

An advanced spam detection model fine-tuned from Gemma 2 2B for WhatsApp chatbots. Capable of identifying spam categories like abusive language, gibberish, and malicious links. Includes training, inference scripts, and configurable settings for customization. 🚀

Build LLM-enabled FastAPI applications without build configuration.

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.

Explore practical fine-tuning of LLMs with Hands-on Lora. Dive into examples that showcase efficient model adaptation across diverse tasks.

MediaPipe samples with Kotlin Multiplatform

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

第八届全国职工职业技能大赛人工智能训练师赛项

Spelling practice, because I think I am dyslexic (Next + Mongo + Prisma + Ollma gemma:2b)

Streamlit App

Invoice OCR Extraction Flask API

Finetune Gemma2b for QA : RAG LoRA ChromaDB

Tools and method for fine-tuning the Gemma 2 model on custom datasets

A Vision Language Model implemented in PyTorch

Welcome to the Exploding Population Myths 1995 repository! This project leverages the Google Gemma model to analyze and debunk common population myths from 1995 book, providing valuable insights into historical population trends.

A chatbot backend application using open-source gemma2:2b LLM model.

A langchain application that use open-source gemma2:2b LLM model.

This project integrates the OpenAI API with a locally running Docker container to generate text completions using the gemma:2b model, as demonstrated in the Jupyter Notebook `ollama.ipynb`.

The task of this project is to Convert Natural Language to SQL Queries