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min-h-wei/Laika
Laika is a text generation model from min-h-wei. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
Laika is a Gemma 4 E2B MobileQAT-derived local model artifact for the Laika macOS app, published as min-h-wei/Laika.
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.safetensors2.5 GB · 99%
How the weights are stored.
U82.1B · 90%
From the Hugging Face model README
Laika is a Gemma 4 E2B MobileQAT-derived local model artifact for the
Laika macOS app, published as min-h-wei/Laika.
This repository is the public-preview model endpoint used by the signed Laika app. It contains the app-ready native MobileQAT bundle:
model.safetensors: packed native MobileQAT weightsconfig.json, tokenizer, processor, generation, and chat-template fileslaika_model_manifest.json: Laika runtime metadataModelReleaseManifest.json: first-use download manifest with file sizes and
SHA-256 hashesThe intended runtime is Laika's native Swift/Metal MobileQAT path
(runtime_backend = mobile_qat_metal). This is not advertised as a generic
drop-in transformers.generate() model; the checked-in config follows Gemma 4
metadata, but the packed weights and quantization layout are meant for Laika's
native loader.
min-h-wei/Laikamin-h-wei/Laika2026.06.21-phaseFmobile_qat_metal65707b8733090dda89f84735f1a1452e7b025f86efab429012b97ab986c4d4838a46ff3ad95d618b42ce514771ca40fadc76a9a448158f8a736b8e521a07293af84fdf6809bdecc43fc2469c4b197e36a63d05feThis preview uses the current app-ready MobileQAT package already on main.
It intentionally does not publish the newer June 30 diagnostic LoRA as the app
model.
The strongest June 30 training artifact is:
src/Model/artifacts/runs/20260630_runtime_residual_hard8_topwrong/04_personal_finance_patch_from_warm_ck48_iters24/lora_ck24.safetensors
That LoRA is a real diagnostic win:
It is not the promoted preview model. The training ledger marks it non-promotable because it is still a Python/native-bridge diagnostic LoRA, not a Swift-loadable native MobileQAT artifact with native parity, product gates, packaged-app smoke, and latency/RSS/swap gates.
These numbers are local Laika gates. They describe this artifact in Laika's runtime path, not general benchmark performance.
| Gate | Result |
|---|---|
| Native runtime smoke | pass |
| Technical-48 | 35 / 48 overall, answer 23 / 36, search 12 / 12 |
| Product-shaped gates | personal raw 58 / 58 with 53 / 53 answers, synthetic base raw 12 / 12, synthetic extended raw 24 / 24, redaction 0 leaks |
| Held-out XPIA | 27 / 27 raw, 27 / 27 citation, 27 / 27 grounding |
| Packaged light UI smoke | first answer about 17s UI-visible / 10.7s request; warm novel answer about 17.4s UI-visible / 10.8s request; exact cached answers under 120ms |
These are preview validation numbers, not customer promises.
SHA-256 checksums for the app-critical bundle files:
efab429012b97ab986c4d4838a46ff3ad95d618b42ce514771ca40fadc76a9a4 model.safetensors
48158f8a736b8e521a07293af84fdf6809bdecc43fc2469c4b197e36a63d05fe ModelReleaseManifest.json
cf6d7dc22738b5e6beb364bac833d78b869f5a6ffd57dfc96c6be3f2abc80424 config.json
cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f tokenizer.json
26fed942f7b9112eff44c145a356d15a9f05b9a6e35e3917a1e70ebba4851f31 laika_model_manifest.json