dusty-nv / jetson-containers
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
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Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
LAVIS - A One-stop Library for Language-Vision Intelligence
🦜🔗 Build context-aware reasoning applications
《开源大模型食用指南》基于Linux环境快速部署开源大模型,更适合中国宝宝的部署教程
Repository to store sample python programs for python learning
面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
MONAI Tutorials
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Kubernetes community content
Google Research
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Official inference library for Mistral models
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.