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Lokai-Sovereign/lokai-mlf-catalog
lokai-mlf-catalog is a machine learning model from Lokai-Sovereign. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for lokai-public-runtime. The card lists the license as other.
Status: public model-distribution repo; the Lokai engine and public stack are coming soon. Generated: 2026-10-28T20:57:11Z
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Updated Oct 28, 2026
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From the Hugging Face model README
Status: public model-distribution repo; the Lokai engine and public stack are coming soon. Generated: 2026-10-28T20:57:11Z
This repository is the model-distribution lane for Lokai MLF packs. The installable list contains only packs that passed the current modular-runtime, provenance, license, installation, and behavior gates. Separately labeled candidate artifacts may be present for qualification; their presence does not make them installable.
Lokai model packs are installed by the Lokai Sovereign Public Stack. They are not standalone Transformers, GGUF, safetensors, PyTorch, or llama.cpp releases. Each pack combines MLF payloads with public-safe metadata for Lokai's modular native runtime.
The model archives are visible under Files and versions. They are runtime packs, not standalone Transformers or llama.cpp models, so downloading one now is useful for inspection but requires the Lokai public stack for execution.
MLF is Lokai's shard-addressable container format. Today it packages model tensors, tensor maps, tokenizer/configuration material, checksums, provenance, and runtime-binding metadata so Lokai can validate and move only the data needed by the selected execution path instead of treating a model as one opaque file.
The container contract is intentionally broader than language-model weights. Typed MLF shards can represent independently verifiable pieces of multimodal models and, as those public runtimes qualify, video, image, and audio data. The same signed, indexed container design is also intended for composable software and operating-system assets. Those future data types are roadmap capabilities, not a claim that every payload is executable in the current preview.
MLF does not remove upstream licenses or provenance. Every published pack keeps its source identity, terms, byte size, and content hashes, and the Lokai runtime must verify those boundaries before activation.
| Model | Runtime ID | Pack size | Intended use | Files |
|---|---|---|---|---|
| Prism Bonsai 27B Q1_0 G128 | prism_bonsai_27b_q1_0_g128 | 3.53 GiB | agentic foreground, compressed capability, conditional vulkan, edge cpu | Browse files |
| Qwen3.6 27B Dense Q4_K | qwen3_6_27b_q4_k_pure | 14.10 GiB | agentic foreground, repo investigation, interactive, large streaming | Browse files |
| Qwen3.8 27B Dense Q4_K | qwen3_8_27b_q4_k_pure | 14.10 GiB | agentic foreground, repo investigation, interactive, frontier dense | Browse files |
Use each row's Browse files link to inspect its archive and manifest in Hugging Face's Files and versions view. Normal users should install packs from Lokai's Models screen rather than downloading and unpacking files manually.
Only packs proven through the modular runtime and product installation gates are published as available. Additional model and hardware support will appear only after passing the same provenance, execution, behavior, and clean-install gates.
These artifacts are approved for anonymous redistribution but remain disabled in the product installer until the stated gate passes.
| Model | Runtime ID | Artifact size | Installation blocker |
|---|---|---|---|
| Qwen3.6 27B Dense BF16 Source | qwen3_6_27b_safetensors_source | 51.77 GiB | modular runtime binding and clean install qualification pending |
| Qwen3.8 27B Dense BF16 Source | qwen3_8_27b_safetensors_source | 51.77 GiB | modular runtime binding and clean install qualification pending |
| Qwen3 4B Instruct 2507 Q8 | qwen3_4b_instruct_2507_q8 | 4.00 GiB | natural use semantic and public placement qualification pending |
| FLUX.1-schnell BF16 | flux1_schnell_native_safetensors | 31.41 GiB | modular generation owner and clean useful artifact qualification pending |
Presence in this table is not runtime promotion, a default-download claim, or public-GA approval.
Lokai Sovereign Public Stackhttps://github.com/Lokai-io/lokaihttps://github.com/Lokai-io/lokaipublic_runtime/public_runtime/weights/packs/active/<model_id>/Downloading a pack without the Lokai public stack does not create a usable Lokai installation. The product supplies validation, device selection, grounding, completion controls, tools, governance, and the deployment-local runtime binding.
https://github.com/Lokai-io/lokai for the engine and public-stack release. The model packs can be inspected now, but they require Lokai for governed execution.No Hugging Face account or token is required for public-GA packs.
Approved pack artifacts are zip archives whose root is public_runtime/. A pack
normally contains:
public_runtime/weights/packs/active/<model_id>/The repository card uses license: other because every pack retains its own
upstream terms. The license and provenance fields in each pack manifest are the
authoritative terms for that artifact.
Pack manifests are designed so the Lokai installer can verify the artifact before making a model selectable.
README.mdcatalog/trusted_model_catalog.jsoncatalog/model_source_registry.jsonThis catalog contains reviewed distribution metadata and approved model-pack artifacts. Model artifacts appear only when redistribution is allowed and the publication workflow binds them to provenance, license, manifest, size, and checksum evidence.
The public stack is intended to be extendable through stable, versioned contracts. Model and backend contributors work against public contracts for manifests, tensor maps, runtime modules, hardware capabilities, receipts, and fail-closed validation. A contribution does not become a trusted public pack merely because it runs locally: it must preserve provenance, pass architecture and capability tests, produce auditable receipts, and complete the community review and maintainer promotion path.
The initial catalog is intentionally narrow so installation remains truthful and
repeatable. Contributor contracts and verification guidance will be published with
the Lokai public stack at https://github.com/Lokai-io/lokai.