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How to run Unsloth in Docker on a GPU server

Use the official Docker image, or the ROCm image for AMD, on a shared server.

Who it is forAn ML engineer setting up a shared training box.

The problemMatching CUDA and library versions by hand is fragile.

The outcomeA containerized Unsloth environment.

What you need first

  • Windows, macOS or Linux, or Docker
  • A GPU for training

Steps

  1. Read the Unsloth Docker guide
  2. Pull the unsloth/unsloth image (unsloth/unsloth-rocm for AMD)
  3. Launch the container with GPU access
  4. Open the UI or notebooks

Prompt for your agent

Start Unsloth from the unsloth/unsloth Docker image on <server> with GPU access and confirm the UI or notebook loads and sees the GPU.

Caveat. Use the unsloth/unsloth:core tag for notebooks only.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for unslothai/unsloth and "Run Unsloth in Docker on a GPU server"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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