Load your first model

The installer seeds slots and starts services — there is no setup wizard in v1.0. Models in hal0 live in a local registry, the single source of truth for Hugging Face coordinates, SHA-256 digests, and curated filenames. Populate it from the dashboard or directly from the CLI.

Via the dashboard

Open the dashboard at http://<host>:8080 and use the Models view to pull a curated pick and assign it to a slot — the largest-that-fits-your-RAM picks are ranked first, with one starred as recommended, filtered to hal0’s curated model catalogue so anything you pick already validates against the registry. Slot assignment happens from the same view: pick a slot, pick a model, apply.

Via the CLI

The Models view — registry, pull progress, and curated loadouts.

The hal0 model subcommand is a thin HTTP client to the API. The common flow is list → pull → assign.

1. List what’s available — registry rows plus models advertised by configured upstreams:

   hal0 model list

   Add --json to emit the raw /api/models payload for scripting.

2. Pull a model from Hugging Face. The argument is either a curated alias (e.g. qwen3-4b) or a registered model id:

   hal0 model pull qwen3-4b

   The pull runs as a background job on the daemon. The CLI polls /api/models/<id>/pull/status every 500 ms and prints a progress bar until the job reaches a terminal state, then reports the final path and SHA-256. If the curated pick is a vision model, its mmproj projector sidecar downloads automatically alongside the main GGUF — no extra step needed.

3. Assign the model to a slot’s default (this does not start the slot):

   hal0 slot edit agent --model qwen3-4b

   This writes model.default into the slot’s configuration. agent is the always-seeded default/anchor slot (see Slots); swap in utility or any other slot name you’ve created instead. Start the slot afterward (see Manage slots).

4. Verify the slot is up:

   hal0 status

   Confirms the slot’s state machine reached its running state with the assigned model loaded.

Other hal0 model commands: add (record an on-disk file in the registry), show (inspect metadata), and rm (remove a registry row).

Gated or large models

Pulls that need a Hugging Face token read HF_TOKEN from the API environment. The easiest path is the dashboard: Settings → Secrets → HuggingFace token applies live without a restart.

When a pull fails

A pull job ends in one of these states: queued, running, completed, failed, or cancelled. On failed, the CLI exits non-zero and prints the error message returned by the daemon; the registry row stays in place so you can retry.

# retry — an already queued/running pull for the same id is reused,
# not duplicated
hal0 model pull qwen3-4b

The dashboard’s Models view surfaces the same failure inline with a Retry button, and you can always pull later from there or via the CLI. Re-issuing a pull for a completed/failed/cancelled job replaces it; a pull already queued or running returns the existing job handle rather than starting a second download.

Next

Once a model is pulled and assigned, you’re ready to send your first chat.