Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
- gpu-acceleration
- large-language-models
- llm
- llm-inference
Repository Index
78,351 visible repositories in the index
337–360 of 1,011 · Most stars
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
- machine-learning
- pattern-classification
- machine-learning-algorithms
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
- navier-stokes-equations
- cfd
- jupyter-notebook
- python
Convert any text to a graph of knowledge. This can be used for Graph Augmented Generation or Knowledge Graph based QnA
Build a modern LLM from scratch. Every line commented. Explained like we are five.
- attention-mechanism
- deep-learning
- educational
- from-scratch
The repository host gives no description.
A collection of guides and examples for the Gemma open models from Google.
- codegemma
- gemma
- paligemma
- recurrentgemma
A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
- anki-addon
- spaced-repetition-algorithm
- anki
- deep-learning
标注自己的数据集，训练、评估、测试、部署自己的人工智能算法
OmniGen2: Exploration to Advanced Multimodal Generation. https://arxiv.org/abs/2506.18871
The repository host gives no description.
Qwen3-omni is a natively end-to-end, omni-modal LLM developed by the Qwen team at Alibaba Cloud, capable of understanding text, audio, images, and video, as well as generating speech in real time.
手把手带你实战 Huggingface Transformers 课程视频同步更新在B站与YouTube
- huggingface
- peft
- transformers
Single Shot MultiBox Detector in TensorFlow
Qwen2.5-Omni is an end-to-end multimodal model by Qwen team at Alibaba Cloud, capable of understanding text, audio, vision, video, and performing real-time speech generation.
Repo for the Deep Learning Nanodegree Foundations program.
The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
- time-series
- time-series-forecasting
- deep-learning
- forecasting
SoTA LLM for converting natural language questions to SQL queries
Homepage for STAT 157 at UC Berkeley
A simplified implemention of Faster R-CNN that replicate performance from origin paper
- pytorch
- object-detection
- faster-rcnn
- voc
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
- 3d
- computer-vision
- dynamic-scene
- gaussian-splatting
Машинное обучение на ФКН ВШЭ