together-gpu-clusters
CommunityProvision GPU clusters on demand for ML workloads.
Authorzainhas
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Provision GPU clusters on Together AI for distributed training and HPC workloads.
Core Features & Use Cases
- Hardware: NVIDIA H100, H200, B200, L40, RTX-6000 with Kubernetes or Slurm orchestration.
- Orchestration: Kubernetes or Slurm, autoscaling, health checks, and multi-node management.
- Management & Accessibility: Python SDK, TypeScript SDK, tcloud CLI, Terraform, SkyPilot, or REST API.
- Storage & Networking: Shared volumes with InfiniBand/nvme-backed storage for high-throughput ML pipelines.
- Use Case: Run large-scale distributed training, batch inference, and HPC simulations with on-demand or reserved capacity.
Quick Start
Create an on-demand Kubernetes GPU cluster by following the Python/TypeScript examples to specify region, GPU type, and cluster size.
Dependency Matrix
Required Modules
togethertogether-ai
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: together-gpu-clusters Download link: https://github.com/zainhas/togetherai-skills/archive/main.zip#together-gpu-clusters Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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