Popular GitHub Repositories for Spot Instances

SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 15+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

Mask3D predicts accurate 3D semantic instances achieving state-of-the-art on ScanNet, ScanNet200, S3DIS and STPLS3D.

[ICCV 2021] Instances as Queries

?? Terraform plugin for machine learning workloads: spot instance recovery & auto-termination | AWS, GCP, Azure, Kubernetes

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

AI-Powered Photo Editor (Python, PyQt6, PyTorch)

Chains stable-diffusion-webui instances together to facilitate faster image generation.

A dataset featuring diverse dialogues between two ChatGPT (gpt-3.5-turbo) instances with system messages written by GPT-4. Covering various contexts and tasks (task-oriented dialogue systems, abstract reasoning, brainstorming).

Fine-tune Facebook's DETR (DEtection TRansformer) on Colaboratory.

Fully automated provisioning of AWS EC2 Spot Instances for Deep Learning workloads using Terraform.

Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)

Source code and datasets of EMNLP2018 paper: "Differentiating Concepts and Instances for Knowledge Graph Embedding".

This repository contains MAPF-GPT, a deep learning-based model for solving MAPF problems. Trained with imitation learning on trajectories produced by LaCAM, it generates actions under partial observability without heuristics or agent communication. MAPF-GPT excels on unseen instances and outperforms state-of-the-art solvers.

Experiment with diffusion models that you can run on your local jupyter instances

Workflow that shows how to train neural networks on EC2 instances with GPU support and compares training times to CPUs

Tune efficiently any LLM model from HuggingFace using distributed training (multiple GPU) and DeepSpeed. Uses Ray AIR to orchestrate the training on multiple AWS GPU instances

Modeling time series of electricity spot prices using Deep Learning.

A Bottom-Up Instance Segmentation Strategy for segmenting document instances using Transformers

Ntfy.sh desktop client for Windows, Linux, and MacOS with push notifications. Supports official ntfy.sh website and self-hosted instances.