/ local coding stack
Point your editor at your own box
Aim any OpenAI-compatible client at :8080/v1 — chat, completions, and a dedicated coder slot. Your code never leaves the LAN, and there's no per-token bill.
1.0.0-rc.4 shipping now · 1.0 GA next
Your Strix Halo box,
running real /v1/*
inference.
hal0 turns a Linux box — ideally aRyzen AI Max+ 395 — into a private, OpenAI-compatible AI appliance: one /v1/*API across every modality, with concurrent workloads the box manages for you. One command installs the lot.
install.sh
$curl -fsSL https://hal0.dev/install.sh | bash
hal0-api:8080 ready·all slots up·GTT 9.2 / 96 GB·probe strix-halo
host strix-halo-01·128 GB UMA · iGPU + XDNA SSE connected
agent
Qwen3-30B-A3B-Instruct-2507-Q4_K_M
serving
142 tok/s
embed
nomic-embed-text-v2-moe-Q4_K_M
serving
116 tok/s
rerank
bge-reranker-v2-m3-q4_k_m
ready
warm
stt
whisper-v3:turbo (NPU)
idle
:8083
tts
kokoro-82M-v1.0
idle
:8084
img
sdxl-turbo
ready
warm
Unified memory (GTT)9.2 / 96 GB carveout · 128 GB DIMM
agent 6.5Gembed 2.3Grerank 0.4Gkernel + ZFS ARC 3.8G
dispatch p50
174ms
/ private knowledge & RAG
Retrieval grounded on your data
Embeddings, reranking, and a bundled agent with opt-in graph memory and MCP tools — a full RAG stack that runs on your hardware, not someone else's server.
/ voice & image lab
Speech and images, one control plane
Transcription, text-to-speech, and local image generation behind the same API — STT on the XDNA NPU, TTS switchable between Kokoro (CPU) and Qwen3-TTS (GPU), ComfyUI on the iGPU, switched cleanly so they share the box.
measured, not claimed
all 26 models · sweep 2026-06-19 →what this box actually does
169.8
fastest decode · tok/s
26
models measured
6248
peak prefill · tok/s
| model | params | decode ▼ | prefill | gb |
|---|---|---|---|---|
| qwen3.5-0.8b | 0.8B | 169.8 | 6248 | 0.6 |
| chadrock3-6-35b-uncensored-mtp-strix-lean | 35B MoE | 102.1 | 890 | 19 |
| chadrock-35b-ace-saber | 35B-A3B | 100.5 | 903 | 19 |
| qwopus3-5-4b-coder-mtp-q6-k | 4B | 85.0 | 889 | 3.6 |
| qwen3.6-35b-a3b-crown-halo-mtp-dynamic | 35B-A3B | 84.4 | 873 | 22.6 |
shared configs
all profiles →start from someone else's tuning
tiny-draft-0-8bdraft
0.6 GB. Not a chat model — the draft half of a speculative pair, pinned so the big model never waits on it.
-ngl 99 -c 2048 -fa 1 -ctk q4_0 --parallel 1 -b 256 --draft-p-min 0.6
169.8tok/sfirst-party
strix-mtp-maxchat
draft-mtp with an f16 KV cache. The fastest tokens this box produces, at the cost of 19 GB resident and no room for a second big slot.
-ngl 99 -c 2048 -fa 1 -ctk f16 -ctv f16 --parallel 1 -b 512 --draft-max 4 --draft-min 1 --mtp on
102.1tok/sfirst-party
coder-next-40bcoding
Sized for autocomplete rather than long generations: 28.5 GB resident, prefill above 750 tok/s so a whole file lands fast.
-ngl 99 -c 8192 -fa 1 -ctk q4_0 -ctv q4_0 --parallel 2 -b 1024
54.7tok/s
@lovedheart
@lovedheartlearn
all posts →latest from the blog
blog · 2026-07-04
What's new in the v0.8 line: Stacks, canonical roles, and voice end-to-end
Config becomes a declarative single source of truth with Stacks, agent/utility replace chat/primary as the canonical roles, voice ships end-to-end behind one engine switch, and a 72-finding reliability sweep lands resumable pulls, disk preflight, and live dashboard telemetry. A look at the v0.8 beta line through v0.8.4b1.
blog · 2026-06-19What's new in the v0.7 line: hal0's first beta
258tok/s
primary + embed concurrent
Strix Halo iGPU · ~9 GB GTT
1call
thundering herd, coalesced
single-flight dispatch + cold-cache prefetch
6workloads
chat · embed · rerank · stt · tts · img
as many slots as memory fits
100tok/s
35B model · MTP speculative decode
ace-saber 35B-A3B · 19 GB · single stream
from the roster benchmark →/ what's in the box
Not another
llama-server wrapper.
Every workload is a real systemd-managed slot with a typed lifecycle. The API surface covers chat and embed and rerank and STT and TTS and image gen. The dashboard is for operating the box — not for chatting with it.
/v1/*
OpenAI-compatible API
chat · completions · embeddings · rerank · transcriptions · speech · images · models. Drop-in for any OpenAI SDK — point your client at :8080/v1 and go.
lifecycle
Typed slot state machine
offline → pulling → starting → warming → ready → serving ↔ idle → unloading. Atomic transitions, persisted to state.json, streamed over SSE.
dispatcher
Single-flight routing
Registry-aware across local slots and external upstreams (OpenRouter, Anthropic, OpenAI, custom). Cold-cache prefetch coalesces a thundering herd into one HTTP call.
probe
Hardware-aware everything
UMA pool on Strix Halo, real CPU/RAM/GPU on WSL2 / Proxmox / bare-metal. Slot-fit warnings size against the real unified pool, not a BAR carve-out.
update
Cosign-keyless self-update
hal0 update --channel stable|preview|nightly. Verified tarballs swap a /usr/lib/hal0/current symlink. --rollback reverts atomically. The 1.0 release candidates ship on the preview channel.
stacks
Declarative Stacks
Plan a slot/model layout into a change set, apply it atomically with rollback, and converge the live slots against it — content-hash drift detection, plus export/import via a checksummed .hal0stack.json envelope.
SLOT LIFECYCLE — ENFORCED IN _transition()
offline→pulling→starting→warming→ready⇄serving⇄idle→unloading→offline↳ error
/ provider stack
Five providers,
one /v1/* surface.
Each provider is stateless — build_env() / start_cmd() / health() / infer(). No global state, no shared connection pool. The picker only advertises a backend the slot can actually honour on your hardware.
Provider
Workloads
Hardware
Endpoints
llama.cppb9279
chat · embed · rerank · vision
Vulkan (default) · ROCm · CUDA
/v1/chat · /v1/embeddings · /v1/rerankings
FLMv1
chat · embed (ASR multiplex)
AMD XDNA NPU (opt-in)
/v1/chat · /v1/embeddings
FLM / Whisperv3 turbo
speech-to-text (co-loaded with chat)
AMD XDNA NPU
/v1/audio/transcriptions
Kokoro / Qwen3-TTS82M · GPU
text-to-speech · one-switch CPU⇄GPU swap
CPU (Kokoro) · ROCm (Qwen3-TTS)
/v1/audio/speech
ComfyUIv1
image gen · SDXL / SD 1.5 / Flux
ROCm
/v1/images/generations
/ hardware
Strix Halo native.
Not Strix-Halo-only.
The probe is UMA-aware on Strix Halo and falls back to portable parsers on every other host. The dashboard only labels memory "unified" when it actually is. Linux + systemd is the only hard requirement.
reference deployment
Ryzen AI Max+ 395
"Strix Halo" iGPU + XDNA NPU + 128 GB LPDDR5X-8000 unified memory
128GB
unified · BIOS-tunable to ~96 GB GPU
258tok/s
primary + embed concurrent
All published perf numbers come from this box. Q4 70B fits with massive headroom; Q4 MoE 100B+ with a 17–22B active path becomes feasible.
first-class
Ryzen AI Max 385 / 390
Strix Halo with 64 GB unified
64GB
unified memory
~70B
Q4 ceiling, shorter context
Same install path. Every small + mid tier fits; 70B Q4 works with tighter context windows.
supported
NVIDIA RTX 30 / 40 / 50
10–32 GB dedicated VRAM · CUDA llama.cpp
32GB
RTX 5090 VRAM ceiling
~30B
Q4 comfortable
Same slot lifecycle, dedicated VRAM instead of UMA — higher tok/s on small models, lower ceiling on the big ones.
supported
AMD Radeon RX 7000
16–24 GB discrete · ROCm or Vulkan container profiles
24GB
7900 XTX VRAM
ROCm
· Vulkan
Discrete AMD path, same hal0-slot@<name> lifecycle as Strix Halo — both ROCm and Vulkan container profiles run today.
fallback
CPU-only x86_64
Vulkan-CPU · usable for tiny models
0.5–4B
practical model size
Qwen0.5B
the CI smoke model
CI runs Qwen 0.5B here. Usable for tiny models and smoke tests, not the headline experience.
supported
Proxmox LXC
privileged container · iGPU + XDNA passthrough
0600
PVE token stored sealed
segmented
host-pressure overlay
Drop a read-only PVEAuditor token into Settings and the memory bar shows physical DIMM total + a muted "Proxmox host" segment for other-tenant + ZFS ARC pressure.
/ recommended loadouts
Curated starting points.
Tweak from there.
Sizes are published file sizes; the slot system takes a different model per slot whenever you change your mind. These are tuned for Strix Halo:A3B MoE models give 30–80B quality at ~3B token-gen speed, and an MTP head on MTP-enabled llama.cpp delivers a measured 1.4–2.4× decode speedup. FP4 is what makes them fit the unified pool — not what makes them fast.
~22 GB · daily-pro28 GB UMA
Your top coder, MTP-fast
primary
Qwopus3.6-27B-Coder-MTPQ6_K · 22.4 GB · MTP head speculates on ROCm — fastest local coder on the box
embed
qwen3-embedding-0.6b-q8Q8 · 0.6 GB · repo-aware code search
~8 GB · lean10 GB UMA
Snappy completion
primary
qwopus3-5-9b-coder-mtp-q6-kQ6_K · 7.6 GB · MTP · fits beside chat + embed
alt
qwopus3-5-4b-coder-mtp-q6-kQ6_K · 3.6 GB · low-VRAM / CPU fallback
~50 GB · max64 GB+ UMA
Coder-Next ceiling
primary
qwen3-coder-next-q4kxlQ4_K_XL · 49.6 GB · dedicated Qwen3-Coder-Next — the quality ceiling
alt
qwen3-coder-reap-25b-a3b-q5kmQ5_K_M · 17.7 GB · validated REAP prune · A3B speed, most of the quality
alt
qwen3-coder-next-reap-40b-a3b-q4kxlQ4_K_XL · 28.5 GB · community 50% prune — unvalidated, some math loss
~15 GB · sweetspot20 GB UMA
The Strix Halo daily-driver
primary
qwopus3-6-27b-v2-mtp-bf16-to-rocmfp4-strix-leanFP4 · 14.8 GB · MTP head + FP4 footprint — a fast 27B that leaves room to spare
embed
nomic-embed-text-v1.5-q8Q8 · 0.1 GB · rides along free
~23 GB · max28 GB UMA
Big-model reasoning at A3B speed
primary
qwen3-6-35b-a3b-halostrix-dyn-mtp-v7Q4 · 22.6 GB · hybrid MoE 3B active · ~69 tok/s with MTP (1.4×)
alt
chadrock-35b-ace-saberROCmFP4 + MTP · 19 GB · uncensored MoE
alt
qwen3.6-27b-heretic-q4kmQ4_K_M · 16.9 GB · vision-capable chat
~8 GB · snappy10 GB UMA
Low-latency, fits anywhere
primary
qwen3.5-9b-deepseek-v4-flash-mtpQ6 · 7.6 GB · MTP flash · fits with embed + voice
alt
lfm2.5-8b-a1b-q6kxlQ6 · A1B MoE · ultra-low-latency, NPU-friendly
~3 GB + NPU · realtime4 GB UMA (+XDNA)
Hands-free, iGPU-free
llm
qwen3.5-4b-q4kxlQ4_K_XL · 2.9 GB · low-latency reply (or gemma4-it-e2b on the NPU)
stt
whisper-v3:turboruns on the XDNA NPU — frees the iGPU for chat
tts
kokoro-v182M · 54 voices · 8 languages
alt
vibevoice-1.5b1.5B · expressive long-form TTS
~16 GB · retrieval22 GB UMA
Grounded synthesis, long context
primary
qwopus3-6-27b-v2-mtp-bf16-to-rocmfp4-strix-leanFP4 · 14.8 GB · fast grounded synthesis at long context
embed
qwen3-embedding-0.6b-q8Q8 · 0.6 GB · strong multilingual retrieval
rerank
bge-reranker-v2-m3Q4_K_M · 0.4 GB · 100+ lang cross-encoder · /v1/rerankings
~7 GB · default12 GB UMA
Photoreal default
img
juggernaut-xl-v9-rundiffusionphoto-v2SDXL · 7.1 GB · photoreal general-purpose checkpoint
alt
sdxl-turboFP16 · 4-step · realtime previews
alt
v1-5-pruned-emaonly-fp162.1 GB · low-VRAM fallback
~17 GB · pro22 GB UMA
Best prompt adherence
img
flux1-dev-fp8FP8 · 17.2 GB · top prompt adherence + legible text
~27 GB · video32 GB UMA
Local text/image-to-video
video
ltx-2-19b-dev-fp8FP8 · 27.1 GB · local video generation on the iGPU
upscale
ltx-2-spatial-upscaler-x22× spatial upscale pass
~25 GB · agentic30 GB UMA
Tool-use + MCP at MTP speed
primary
qwen3-6-35b-a3b-halostrix-dyn-mtp-v7Q4 · 22.6 GB · MoE A3B · strong tool-calling, MTP-fast
alt
hermes-4-14b-q5kmQ5_K_M · 10.5 GB · Hermes-4, tuned for tool-call faithfulness
embed
qwen3-embedding-0.6b-q8Q8 · 0.6 GB · retrieval-augmented routing
mcp
/mcp/admin + /mcp/memoryHindsight graph memory · two-tier scope
~11 GB · lean14 GB UMA
Lean tool-caller
primary
hermes-4-14b-q5kmQ5_K_M · 10.5 GB · tool-call faithful, fits beside a coder
alt
gpt-oss:20bMoE · strong tool-use + reasoning
<1 GB · minimalCPU OK
Privacy-first tiny
primary
qwen3.5-0.8b0.6 GB · sub-second cold start · smoke-test / lite
embed
nomic-embed-text-v1.5-q8Q8 · 0.1 GB
~0 iGPU · npuXDNA only
NPU-only, zero iGPU
llm
gemma4-it-e2b-FLMruns entirely on the XDNA NPU — iGPU stays free
stt
whisper-v3:turboNPU transcription
embed
embed-gemma-300m-FLMNPU embeddings
~2 GB · minimal-coder4 GB UMA
Tiny coder
primary
qwopus3-5-4b-coder-mtp-q6-kQ6_K · 3.6 GB · MTP autocomplete
alt
qwen3-zero-coder-v2-0.8b-f16F16 · 1.6 GB · smallest coder
Model ids are real, pull-able registry ids. Considering Apache-clean upgrades? Qwen-Image (beats FLUX on prompt + text rendering), Qwen3-Reranker-0.6B (pairs with the Qwen3 embedder), and Chatterbox-Turbo (zero-shot voice cloning) are easy pulls when you want them.
/ vs. the alternatives
hal0 isn't an inference engine —
it's the orchestration around one.
Slots survive hal0-api restarts. Embeddings, rerank, STT, TTS, and image gen all sit behind the same/v1/* surface. UMA-aware hardware probe and slot-fit warnings are first-class — not a slash command in a chat window.
hal0 (this)
ollama
LM Studio
OpenAI cloud
OpenAI-compatible /v1/*
chat · embed · rerank · STT · TTS · img
chat · embed
chat · embed
chat · embed · STT · TTS · img
Concurrent slots
as memory fits
one at a time
one at a time
fully concurrent
Slot lifecycle state machine
typed, atomic, SSE-streamed
no
no
—
UMA-aware hardware probe
Strix Halo · NPU · platform-aware
CPU / GPU only
CPU / GPU only
—
XDNA NPU support
first-class via FLM
no
no
—
Dispatcher with upstreams
OpenRouter · Anthropic · OpenAI · custom
no
no
—
Cosign-signed updates
keyless OIDC + rollback
no
auto-update
—
Headless / Linux-first
systemd-required, headless
cross-platform
GUI required
cloud
Your data, your hardware
yes
yes
yes
no
Cost per million tokens
$0 + electricity
$0 + electricity
$0 + electricity
$0.50 – $60
Competitor capabilities reflect each project's published docs as of June 2026 and move fast — treat this as a snapshot, not a live scorecard.
/ the console
Chat, image gen, agents, and memory —
one console.
Slots, models, local image generation, graph memory, an agent task board, MCP, and logs — every surface in one React operator console. SSE-backed, dark by default. Real screenshots from a live hal0 instance.
Plus a Hermes agent that lives on the box, an Operator Board kanban wired to it, an MCP server + client, and a live XDNA NPU view — see theroadmap for everything shipped.
/ the bundled agent
An agent that
lives on the box.
Hermes installs and bootstraps itself on first run — sandboxed under its own user, prewired to the local /v1 API and your MCP servers, with opt-in graph memory. Reach her from Telegram or Discord; she chains tools for hours fully AFK and folds every run back into memory.
- Self-bootstraps: env probe → model wiring → MCP memory → persona.
- Sandboxed
hal0-agent@hermes.service— own user, no new privileges. - Gated tools clear an approval bell; every call is audited.
Agents & memory →hover to tilt · click to flip
Hermes
chadrock-35b-ace-saberctx0/164K
remote control · self-improving · orchestration
Hermes · abilities
Ghost Relay40pwr
Summon her from any Telegram or Discord thread.
Engram60pwr
Folds every run back into memory — never relearns.
Deep Run90pwr
Chains tools for hours, fully AFK.
Skills
voice · ttsspeech · sttimage-genvisionembeddings
logspersona
Run agents →/ roadmap
One service for the
whole local AI stack.
No dates. Each themed row reads left-to-right: shipped, in flight, exploring — the closer to the left, the closer it is to running on your box. Tagged versions ship toreleases.hal0.dev within ~60s.
180 agent-reachable admin tools, honest slot lifecycle, device-keyed voice —
hardened across three release candidates.
01
mcp
The whole platform is agent-reachable
The admin MCP catalog grew from 92 to 180 tools — services, ComfyUI, updater/doctor/health, telemetry, slots, models, bench, approvals — plus a 26-tool memory surface at feature parity with Hindsight 0.8.4.
02
slots
Slots start when you say so
A new autoload setting decouples binding a model from boot start, and an eviction priority (0–100) replaces the inert lru opt-in — memory-pressure eviction actually works on a stock box. On-demand capability slots and per-slot profiles round it out.
03
voice
Voice is a device-keyed switch
Moonshine returns as the CPU STT engine in its own toolbox image: cpu runs Moonshine, npu runs whisper-v3:turbo, and GPU honestly resolves to no STT engine instead of silently taking a llama chat profile.
04
hardening
rc.3 — the hardening candidate
38 changes from the pre-1.0 review, every one a defect fix, dependency bump, or doc correction landed with a red-first test: the update path works end-to-end on real hosting, id-keyed boxes are first-class, and the memory surfaces tell the truth.
01
shipped
running on your box today
02
in flight
targeting the 1.0 line
03
exploring
bets, not promises
Inference + providers
The /v1/* surface and the engines behind it.
4/0/2
✓
OpenAI-compatible /v1/* API
Chat, completions, embeddings, rerank, transcriptions, speech, images. Every OpenAI SDK works unchanged against the local box.
✓
Five-provider stack
llama.cpp (Vulkan / ROCm) for chat and embed, FLM for the XDNA NPU (chat + whisper-v3:turbo STT + embed, one process), Kokoro (CPU) or Qwen3-TTS (GPU) behind a one-switch tts slot, ComfyUI for image generation.
✓
Image generation + iGPU switchover
POST /v1/images/generations served by a ComfyUI engine; generating flips the GPU into exclusive image mode and back, so chat and image share one accelerator.
✓
FLM NPU provider
Self-contained NPU toolbox pinned by digest. The chat + STT + embed trio is surfaced only when XDNA hardware is present.
—nothing queued
◦
Fine-tune & LoRA hot-swap
Attach and rotate LoRAs against a warm base model without unloading the underlying weights.
◦
Per-model rate limits & budgets
Cost-style accounting for local inference so a chatty agent can be capped without taking the whole box down.
Slot lifecycle
Atomic transitions, honest health, no snapshots.
3/1/0
✓
Slot lifecycle state machine
Atomic transitions (offline → pulling → starting → warming → ready → serving), persisted and SSE-streamed.
✓
Honest slot health + derived context
A slot is marked ready only once its real /health passes — never on a systemd snapshot. Context size is derived per slot, never silently inheriting the 4096 default.
✓
Capability slots + profiles
Embed / Voice / Image capability cards and an NPU rollup over flat slots; per-device profiles unify the launch flags, all from one Slots tab.
◇
Benchmarks & presets UI
In-dashboard tok/s + latency runs, plus curated loadout presets you can flash onto a fresh install.
—nothing queued
Install + distribution
One command. Signed. Resumable.
3/1/0
✓
hal0 setup TUI
A terminal first-run wizard: pick a hardware-anchored tier, storage, extensions, and models, then it provisions a coherent set of slots — or run --auto for recommended defaults.
✓
Cosign-signed self-update
Atomic version swap with one-flag rollback. Stable, preview, and nightly channels, GitHub OIDC-verified release tarballs, manifest proxied at releases.hal0.dev.
✓
Extensions framework
Apps and agents (Open WebUI, ComfyUI, Hermes, Pi) packaged as auto-wired extensions: lifecycle-managed, selectable at setup.
◇
AUR PKGBUILD & Ubuntu PPA
Native distro packages on top of the install script: pacman and apt as first-class install paths.
—nothing queued
Hardware + observability
Probe before you load. A memory bar that tells the truth.
3/0/1
✓
UMA-aware probe
Detects iGPU, XDNA NPU, and the unified memory pool; surfaces fit warnings inline before you load a model that won't fit.
✓
Live GTT total + honest memory bar
The memory bar reports the live GTT total from the driver, not a stale cached probe — so the unified pool you see is the pool you have.
✓
NPU occupancy grid
A living per-slot occupancy view of the XDNA NPU that breathes with real activity instead of a static picker.
—nothing queued
◦
Multi-host federation
A slot mesh across LAN boxes: chat on the Strix Halo, embed on the workstation, all behind one /v1/* surface.
Agents + memory + MCP
A place for agents to live, not only to chat with.
4/0/1
✓
Bundled Hermes agent
Hermes installs and bootstraps on first run — sandboxed under its own user, prewired to the local /v1 API and MCP servers, with an agent-card library in the dashboard.
✓
Operator Board
A hal0-skinned kanban wired to Hermes (/api/board/*), with a live agent-chat drawer and working task creation.
✓
Hindsight graph memory
Opt-in memory engine (HAL0_MEMORY_ENABLED). Shared by default; the X-hal0-Agent header scopes a client's writes to its own namespace. Every destructive op — bank delete, memory/document/directive wipes — now records a durable, attributable audit row.
✓
MCP host + server
hal0 speaks Model Context Protocol both directions: an admin + memory MCP server, plus an allow-listed client that composes external MCP tools. Destructive calls gate through an approval bell + CLI.
—nothing queued
◦
ChatOps adapters
Slack and Matrix bridges as extensions, so you can talk to hal0 from the rooms you already live in.
Security posture
No bundled auth — open on the LAN by default; front it with your own proxy.
3/0/0
✓
Open by default, proxy at the edge
No bundled auth or TLS (ADR-0012): the API binds 0.0.0.0:8080 for the LAN. Expose it by putting your own reverse proxy — Traefik, nginx, or a Cloudflare Tunnel — in front.
✓
Bundled chat UI + voice
Open WebUI on :3001 prewired to the local API, whisper-v3:turbo STT (NPU, via FLM), and a one-switch Kokoro (CPU) ⇄ Qwen3-TTS (GPU) TTS engine served through the capability API.
✓
Hands-free voice via Open WebUI Call mode
Open WebUI's built-in Call mode wired to hal0's /v1/audio/transcriptions and /v1/audio/speech endpoints — whisper-v3:turbo for listen, Kokoro for reply. No native hal0 streaming orchestrator; the loop runs inside Open WebUI.
—nothing queued
—nothing queued
※Exploring items are bets we believe in, not promises. Scope and order will shift release to release — 1.0 GA is next — as we learn what people actually do with a local platform.open an issue ↗
/ get hal0
Stop running models
from a chat tab.
One command on a fresh Linux box. hal0's 1.0 line is at release-candidate stage — GA is next — and it installs and runs the whole stack today.
install.sh
$curl -fsSL https://hal0.dev/install.sh | bash
Apache-2.0Linux + systemdno telemetry by defaultcosign-signed releases