deploy-dia

deploy-dia is a skill for Claude Code, Codex from Seeed-Projects/Seeed-Jetson-DevelopTool. It costs 78 tokens per session (1,063 once invoked), scanned B, original, MIT.

A deployment guide for Dia, a speech-generation model that turns text into expressive audio with multiple speakers, on a reComputer Jetson. It launches the model through a Gradio web interface, a browser-based control screen.

In plain words
What is it for?
Installing the required ARM64 Python packages, downloading the Dia code, adjusting its project configuration, and launching a web UI for generating multi-speaker speech. It requires 8 GB or more of RAM and JetPack 6.1 or later.
Why use it?
It handles the Jetson-specific installation of PyTorch, audio libraries, and Triton, which are needed to run the model on its processor architecture. It also prepares the source code and starts the interface.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Installing the required ARM64 Python packages, downloading the Dia code, adjusting its project configuration, and launching a web UI for generating multi-speaker speech. It requires 8 GB or more of RAM and JetPack 6.1 or later.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/seeed-projects/seeed-jetson-developtool/deploy-dia
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Seeed-Projects/Seeed-Jetson-DevelopTool --skill deploy-dia
Clone the repo
git clone --depth 1 https://github.com/Seeed-Projects/Seeed-Jetson-DevelopTool

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for deploy-dia

README.md
[![agentmods](https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/deploy-dia/github.svg)](https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-dia)
Your own site
<a href="https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-dia"><img src="https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/deploy-dia/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for deploy-dia

Your own site · 80×15
<a href="https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-dia"><img src="https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/deploy-dia.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,063 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Privilege Escalation · line 105
    Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
    Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00078 $0.01063
Opus 5.5 $0.00031 $0.00425
Sonnet 5.5 $0.00016 $0.00213
Haiku 4.5 $0.00008 $0.00106

Measured 1mo ago against content hash 832a3cc2f651, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

deploy-dia scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

| Gradio WebUI not accessible remotely | Confirm `GRADIO_SERVER_NAME=0.0.0.0` is set. Check firewall: `sudo ufw allow 7860`. |
seeed_jetson_develop/skills/openclaw/deploy-dia/SKILL.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.


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.

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

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.


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.

Read the full file on GitHub · 114 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 114 lines · 78 tokens per session scan B 832a3cc2f651

Subscribe to this mod's changes

deploy-dia is a skill published in the GitHub repository Seeed-Projects/Seeed-Jetson-DevelopTool (56 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 1,063 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

spark-environment-setup

Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.

wshobson/agents · 76 tokens

spark-memory-thermal-ops

Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.

wshobson/agents · 59 tokens

spark-training-gotchas

Preflight and diagnose the ten known failure modes for ML training on NVIDIA DGX Spark. Use when a training run on DGX Spark fails to start, OOMs below the 128GB limit, slows down mid-run, or before any multi-hour training job on GB10.

wshobson/agents · 63 tokens

inference-serving-llama-cpp

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

davila7/claude-code-templates · 80 tokens

amc-run-rtsp-calibration

Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.

NVIDIA/skills · 59 tokens

deepstream-generate-pipeline

Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image inference, detection, tracking, or streaming — including natural phrases like 'pipeline to infer on image', 'run inference on video', 'detect objects in stream', 'save inference output', 'deepstream pipeline'…

NVIDIA/skills · 108 tokens