Installation

There are three ways to install Miles. Docker is recommended because Miles pins patched versions of SGLang, Megatron-LM, and a few CUDA kernels.

Method 1: Docker (recommended)

NVIDIA
AMD MI300X / MI350X

docker pull radixark/miles:latest

docker run --rm \
  --gpus all --ipc=host --shm-size=32g \
  --ulimit memlock=-1 --ulimit stack=67108864 \
  --network=host \
  -it radixark/miles:latest /bin/bash

docker pull rlsys/miles:MI350-355-latest    # or MI300-latest

docker run --rm \
  --device /dev/dri --device /dev/kfd \
  --group-add video --ipc=host --shm-size=32g \
  --cap-add SYS_PTRACE --security-opt seccomp=unconfined \
  --privileged \
  -it rlsys/miles:MI350-355-latest /bin/bash

The image ships with:

PyTorch (matching the container’s CUDA / ROCm version)
Megatron-LM, SGLang, FlashAttention-3, DeepGEMM, Apex
Ray, uv, and Miles installed editable at /root/miles

See Platforms for platform-specific notes.

Method 2: From source

Clone and install in an existing environment.

git clone https://github.com/radixark/miles.git
cd miles
pip install -r requirements.txt
pip install -e . --no-deps

Patched dependencies. Miles pins patched versions of SGLang and Megatron-LM. Installing them yourself at the wrong commit is the most common source of bug reports — use Docker if you can.

Method 3: Update an existing container

If you already run a Miles image and want the latest code:

cd /root/miles
git pull --rebase
pip install -e . --no-deps
ray stop && ray start --head --port=6379

Verify

Confirm Miles imports and the GPUs are visible:

python -c "import miles; print('Miles import OK')"
nvidia-smi

If either command fails, see Debugging or the FAQ.

Hardware requirements

Hardware	Status
NVIDIA H100 / H200	Production (CI guarded)
NVIDIA B100 / B200	Production
NVIDIA A100	Supported — FP8 features disabled
AMD MI300X, MI325, MI350X, MI355X	Supported via ROCm

For multi-node training you also need a high-bandwidth interconnect — InfiniBand, RoCEv2, or Slingshot — and 200+ GB/s per node. Single-node jobs run fine over NVLink only.

Next steps

Quick Start — run your first training job.
Core concepts — the mental model behind Miles.
Training backends — Megatron vs FSDP.

​Method 1: Docker (recommended)

​Method 2: From source

​Method 3: Update an existing container

​Verify

​Hardware requirements

​Next steps

Method 1: Docker (recommended)

Method 2: From source

Method 3: Update an existing container

Verify

Hardware requirements

Next steps