What is This Skill?
This skill teaches AI coding agents how to deploy custom Docker containers on Together AI's managed GPU infrastructure. Bring your own inference code, custom models, or specialized ML pipelines — Together AI handles the GPU provisioning and orchestration.
Answer-Ready: Together AI Dedicated Containers Skill for coding agents. Deploy custom Docker inference workers on managed GPUs. Full environment control with Together AI infrastructure. Part of official 12-skill collection.
Best for: ML teams with custom inference requirements. Works with: Claude Code, Cursor, Codex CLI.
What the Agent Learns
Deploy Container
from together import Together
client = Together()
container = client.containers.create(
image="your-registry/custom-model:latest",
hardware="gpu-h100-80gb",
replicas=2,
env={"MODEL_PATH": "/models/custom", "MAX_BATCH_SIZE": "32"},
ports=[8080],
)Use Cases
| Scenario | Why Containers |
|---|---|
| Custom models | Non-standard architectures |
| Custom preprocessing | Domain-specific pipelines |
| Multi-model serving | Ensemble inference |
| Compliance | Controlled environment |
Container Management
# Update
client.containers.update(container.id, replicas=4)
# Logs
logs = client.containers.logs(container.id)
# Delete
client.containers.delete(container.id)FAQ
Q: What GPU types are available? A: H100, H200, and A100 GPUs. Contact Together AI for B200 availability.