A Framework of Small-scale Large Multimodal Models
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Updated
Apr 26, 2025 - Python
A Framework of Small-scale Large Multimodal Models
A simple Python script for running LLMs on Intel's Neural Processing Units (NPUs)
This application allows users to upload PDF files, process them, and ask questions about the content using a locally hosted language model. The system uses Retrieval-Augmented Generation (RAG) to provide accurate answers based on the uploaded PDFs.
Most simple and minimal code to run an LLM chatbot from HuggingFace hub with OpenVINO
An offline AI-powered chatbot built using Streamlit and TinyLlama. It responds to your messages in real-time without needing internet access. Great for experimenting with lightweight local language models.
A real-time offline voice-to-voice AI assistant built for Raspberry Pi
This project is a chat application with a web interface developed using Streamlit and a backend developed with FastAPI. Use LLM TinyLlama Model as chat assistant.
Terminal Commander AI is a smart, natural language terminal assistant that converts English instructions into safe, executable shell commands. It supports ROS operations, multi-terminal launching, command explanations, and history — powered by a local TinyLlama LLM.
This project is a Multi-Agent AI System that assists farmers by providing AI-driven crop recommendations, market analysis, and real-time weather insights by the use of Ollama AI, WeatherAPI, and SQLite3, it optimizes resource usage, reduces costs, and maximizes profits—ensuring sustainable and data-driven agriculture.
Sophisticated multi-agent system combining natural language processing with ROS integration and scientific analysis using optimized open-source LLMs.
SummarAIze 🤖✨ — An AI-powered summarization app that transforms lengthy product reviews and web pages into concise, human-like summaries. Built with Flask, T5, and TinyLlama, it scrapes, summarizes, and refines text for clear, natural output. Perfect for quick insights, research, and time-saving content analysis.
Quantize TinyLlama-1.1B-Chat from PyTorch to CoreML (float16, int8, int4) for efficient on-device inference on iOS 18+.
A Retrieval-Augmented Generation (RAG) chatbot using FastAPI, FAISS, and TinyLlama — fine-tuned via LoRA for domain-specific question answering on Indonesian mental health and policy.
Quantize TinyLlama-1.1B-Chat from PyTorch to CoreML (float16, int8, int4) for efficient on-device inference on iOS 18+.
ローカル環境でGGUF形式のLLMを実行するPythonアプリケーション(llama.cppベース)
Fine-tune a lightweight LLM (TinyLlama-1.1B) for bioinformatics instruction-response tasks using LoRA. Compare model performance before and after fine-tuning on domain-specific prompts. Fully compatible with Apple M1/M4 (Metal GPU) and demonstrates end-to-end fine-tuning, inference, and adapter merging.
Smart home system to control smart devices using natural language commands. Using the planning and processing capabilites of LLMs
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