Double Quantization Experiment: Quantizing a Quantized model for On-device Deployment
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Updated
Jul 1, 2024 - Jupyter Notebook
Double Quantization Experiment: Quantizing a Quantized model for On-device Deployment
This project implements a complete offline RAG-Fusion application for text generation and retrieval, leveraging efficient local resources.
Firebase MLkit vision demo app
Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
SponsorMe is a project to help provide access to digital tools for learning, powered by on-device machine learning, innovation and willingness, to those people that have limited access to technology due to demographics, disabilities, economy or other multiple reasons.
2022 D.Com 동아리 대항전 Team "AEye" - Android Native App 개발을 위한 Repo.
A python framework for designing high-performance Computer Vision pipelines at the Edge. Supports Coral Edge TPU, Raspberry Pi Camera, and more.
Hugging Face Transformers.js wrapper for on-device AI with web-workers
BLOCKSET: Efficient out of core tree ensemble inference
A Google Photos alternative, where your pictures never leave your phone! Classification happens on-device, leveraging pre-trained models. Available for Android and iOS.
Object detection inference with Roboflow Train models on NVIDIA Jetson devices.
Kotlin bindings for Edgerunner
Binary Neural Network on IceStick FPGA.
Simplified AI runtime integration for mobile app development
Recipes for on-device voice AI and local LLM
This is a web demo for camera-based PPG sensing (rPPG).
Build Trust with Responsible AI Use 🌱🤝
Source code for my blog post series "On-device training with Core ML"
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