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Find models in the registry, pin versions, and pull weights locally.

Once a model is in the registry, anyone in the organization (and every org, for public models) can find it, pin a version, and pull it. The Hub and the CLI are two views of the same data.

List models in your organization

Section titled “List models in your organization”
Terminal window
dn model list
acme/[email protected]      private - 7B assistant fine-tuned on support tickets.
acme/[email protected] private - LoRA adapter for Llama-3.1-8B-Instruct, rank 16.
acme/[email protected]      public  - DistilBERT intent classifier.

Add --include-public to see every organization’s public models alongside yours:

Terminal window
dn model list --include-public

--search <text> filters on name or description; --limit N caps the result count; --json emits the raw response for scripting.

Inspect a model

Section titled “Inspect a model”
Terminal window
dn model info acme/support-assistant
acme/[email protected] private - 7B assistant fine-tuned on support tickets.
  versions: 1.2.0, 1.1.0, 1.0.0, 0.1.0

info shows the latest version’s summary and the full version history. Pass a specific version to fetch that record (dn model info acme/[email protected]). Use --json to see the full manifest payload — tags, base model, license, and the aliases attached to each version.

For a side-by-side view with metrics, aliases, and sizes across 2–5 versions, use dn model compare — see Versions & metrics.

Pinned references

Section titled “Pinned references”

org/name@version is the canonical way to refer to a model. Every downstream consumer resolves this same shape:

WhereExample
Training base modelbase_model: acme/[email protected] in model.yaml
SDK pulldn.pull_package(["model://acme/support-assistant:1.2.0"])
SDK loaddn.load_package("model://acme/[email protected]")
CLI pulldn model pull acme/[email protected]

Omit @version for “latest visible” — handy for interactive inspection, but avoid it in automation. A moving latest turns reruns into moving targets. Prefer an alias (@champion) for human-readable promotion and a pinned version for reproducible runs.

When the model lives in your own organization, the org/ prefix is optional. The CLI and SDK resolve bare names against your active org.

Pull a model locally

Section titled “Pull a model locally”

The SDK pulls the full directory into local storage and makes it available to Model:

import dreadnode as dn
from dreadnode.models import Model


dn.pull_package(["model://acme/support-assistant:1.2.0"])
model = Model("acme/support-assistant", version="1.2.0")

See Using in code for loading weights and tokenizers.

The CLI’s dn model pull issues a pre-signed download URL — useful for an out-of-band fetch or a browser download:

Terminal window
dn model pull acme/[email protected]
# Download URL (expires 2026-04-21T18:23:00Z):
# https://...

Add --output <path> to save the download directly instead of printing the URL:

Terminal window
dn model pull acme/[email protected] --output ./support-assistant.safetensors

The SDK path is the right choice when you plan to load the weights from Python. Reach for dn model pull when you want a raw artifact on disk without a Python session.

Browse in the Hub

Section titled “Browse in the Hub”

The Hub shows the same listings with facet filters (tags, license, task categories, framework, size category), a per-version detail panel with framework, base model, metrics, and aliases, and the full version history with comparison charts. Authoring happens through the CLI or SDK; discovery happens through either.

What to reach for next

Section titled “What to reach for next”