Popular GitHub Repositories for Nikul Ram

Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RISC-V supported. Accelerated by XNNPACK.

Explore large language models in 512MB of RAM

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Keras Implementation of Aspect based Sentiment Analysis

Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.

A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

? Open-source project for creating high-quality AI TTS-narrated audiobooks at home using models like Zonos, Kokoro-82M, or services like Deepgram and Eleven Labs. Tested on Apple Silicon M1 (32GB RAM). ??

[ACL 2024] This is the code for our paper ”RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records“.

⚡ A single‑binary Go microservice that exposes a First‑In First‑Out message queue completely in RAM.

An advanced autonomous drone navigation system using complex technologies in computer vision and AI for real-time obstacle detection, environmental interaction, and adaptive flight path management. Designed for enhanced security and efficient navigation.

Recognize Anything Model (RAM) image recognition for ComfyUI

RAM-VO: A Recurrent Attentional Model for Visual Odometry.

Just an UI for Chatterbox, which uses about 1-2 GB RAM. Double click and you're good to go.

Predicting the temperature of your system based on factors such as RAM usage,CPU storage temperature,Memory Used and space consumed by the applications( CPU load).

Supervised ML- Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. Model will predict the price range indicating how high the price is.

Tradeoff between runtime and RAM usage for large language model inference.

This repo analyzes Open Source Diffusion models for generating photorealistic images, focusing on criteria like execution time, CPU/RAM usage, photorealism, steerability, and resource optimization to identify the most efficient pipeline for high-quality image production.

Localy deploy Stable Diffusion x4 image upscaler with Windows 10+ GUI. Includes smart features that dramatically reduce RAM/VRAM requirements over similar implementations.

A general and accurate RAM / MACs / FLOPs profiler for ONNX models (Currently work-in-progress)