Popular GitHub Repositories for 350 Million Parameters

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

A Streamlit-powered Chat Assistant utilizing Ollama's DeepSeek-R1 (1.5B) model for intelligent, context-aware conversations. Designed with an interactive chat interface, adjustable model parameters. It leverages Ollama for local model serving and Streamlit for a responsive UI for text-based interactions.

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

A Julia machine learning framework

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

Official Pytorch implementation of the preprint paper "Stylized Neural Painting", in CVPR 2021.

Open-source implementation of Google Vizier for hyper parameters tuning

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A fast and powerful image/video browser for Stable Diffusion webui / ComfyUI / Fooocus / NovelAI / StableSwarmUI, featuring infinite scrolling and advanced search capabilities using image parameters. It also supports standalone operation.

A project for processing neural networks and rendering to gain insights on the architecture and parameters of a model through a decluttered representation.

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)

This extension is developed for AUTOMATIC1111's Stable Diffusion web UI that provides import/export options for parameters.

[ECCV 2024 - Oral] ACE0 is a learning-based structure-from-motion approach that estimates camera parameters of sets of images by learning a multi-view consistent, implicit scene representation.

HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!

Implementation of MEGABYTE, Predicting Million-byte Sequences with Multiscale Transformers, in Pytorch

[ICLR2025 Spotlight?] Official Implementation of TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters

? [BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.