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Hi there 👋

I'm a third-year Computer Science Undergraduate student from India.

  • 🔭 I’m currently working on improving the OpenVINO Toolkit
  • 😄 I love working with neural networks
  • 🌱 My interests involve DL, LLMs and just a touch of Web Development
  • ✨ I'm big on promoting open-source adoption
  • 📫 Feel free to reach me through email or Linkedin

Siddhant Chauhan's Projects

ai-byte icon ai-byte

Fullstack Web App made using Gin framework for GO and Next.JS 13 Teaches that evaluates AI knowledge using OpenAI Platform

appsmith icon appsmith

Framework to build admin panels, internal tools, and dashboards. Integrates with 15+ databases and any API.

audiocraft icon audiocraft

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.

chat-app icon chat-app

This is the GitHub repository of my CS Project: Encrypted Chat App

edgeml icon edgeml

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

jiit-web-app icon jiit-web-app

Web-App for retrieving Attendace (and more) from JIIT Web-Kiosk In development

jobsnap icon jobsnap

A platform that makes temporary work one click away

nncf icon nncf

Neural Network Compression Framework for enhanced OpenVINO™ inference

offline-qr-code icon offline-qr-code

📱 Browser add-on allowing you to quickly generate a QR code offline with the URL of the open tab or other text!

openagent icon openagent

Microservices approach to AGI. Modular components for AI apps or AGI agents. (... and solving some wicked LLM problems like ⚡ 2X speedup for LLaMA)

openvino icon openvino

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

ray icon ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

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