deploy-dia

name	deploy-dia
description	Deploy the Dia neural text-to-speech model on reComputer Jetson for expressive, multi-speaker audio generation. Installs custom aarch64 PyTorch/torchaudio/triton wheels, clones the Dia repo, patches pyproject.toml, and launches a Gradio WebUI. Requires Jetson with 8GB+ RAM and JetPack 6.1+.

Deploy Dia TTS on reComputer Jetson

Dia is an expressive neural speech generation model that produces natural multi-speaker audio from text. This skill deploys it on Jetson with a Gradio web interface.

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Execution model

Run one phase at a time. After each phase:

• Relay all output to the user.
• If output contains [STOP] → stop immediately, consult the failure decision tree.
• If output ends with [OK] → tell the user "Phase N complete" and proceed to the next phase.

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Prerequisites

Requirement	Detail
Jetson device	8GB+ RAM (e.g. reComputer J4012 with Orin NX 16GB)
JetPack	6.1 or later
Python	3.10 with pip
Network	Internet access for downloading wheels and cloning repo

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Phase 1 — Download and install aarch64 PyTorch wheels (~5–10 min)

Download the following wheels from the Seeed shared drive:

• torch-2.7.0-cp310-cp310-linux_aarch64.whl
• torchaudio-2.7.0-cp310-cp310-linux_aarch64.whl
• triton-3.3.0-cp310-cp310-linux_aarch64.whl

Install them:

pip install torch-2.7.0-cp310-cp310-linux_aarch64.whl
pip install torchaudio-2.7.0-cp310-cp310-linux_aarch64.whl
pip install triton-3.3.0-cp310-cp310-linux_aarch64.whl

Verify:

python3 -c "import torch; print(torch.__version__); print('CUDA:', torch.cuda.is_available())"

[OK] when torch imports and CUDA is available. [STOP] if wheel install fails.

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Phase 2 — Clone Dia and patch dependencies (~2 min)

git clone https://github.com/nari-labs/dia.git
cd dia

Edit pyproject.toml to comment out the torch, torchaudio, and triton dependency lines (lines 19–22) since we installed custom Jetson wheels:

sed -i 's/^\(\s*"torch.*\)/#\1/' pyproject.toml
sed -i 's/^\(\s*"torchaudio.*\)/#\1/' pyproject.toml
sed -i 's/^\(\s*"triton.*\)/#\1/' pyproject.toml

Install Dia and fix numpy:

pip install -e .
pip install numpy==1.26.4

[OK] when pip install -e . completes without error. [STOP] if dependency resolution fails.

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Phase 3 — Launch Dia Gradio WebUI (~2 min to start, model download on first run)

export GRADIO_SERVER_NAME=0.0.0.0
cd dia
python app.py

Open a browser and navigate to http://<jetson-ip>:7860.

[OK] when the Gradio interface loads and you can generate audio from text.

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Failure decision tree

Symptom	Action
Wheel install fails — platform mismatch	Confirm you are on aarch64 with Python 3.10: python3 --version and uname -m.
import torch fails after install	Check pip target: python3 -m pip show torch. Ensure no conflicting system torch.
CUDA not available in torch	Verify JetPack 6.1+ is installed: cat /etc/nv_tegra_release. Check nvcc --version.
pip install -e . fails on dependency	Ensure torch/torchaudio/triton lines are commented out in pyproject.toml.
Gradio WebUI not accessible remotely	Confirm GRADIO_SERVER_NAME=0.0.0.0 is set. Check firewall: sudo ufw allow 7860.
OOM when generating audio	Close other GPU processes. 8GB is minimum — larger models may need 16GB.
Model download hangs on first run	Check internet connectivity. Retry or manually download model weights.

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Reference files

• references/source.body.md — Full Seeed Wiki tutorial with screenshots, demo video, and sample dialogue text (reference only)