Models › laya-typed family

laya-typed-decisions

convaiinnovations Apache 2.0 out 37 days ago

421M parameters, text in, labels out.

Verified 2026-10-25 Rank #0 in Decision models · score 0 method v1 Sources 3 Downloads 30d 3.8k · #558 of 619 tracked

Changed this week: 2 new quantized builds on the Hub (16 in all).2026-10-24

Can I run it?0.3GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?3.8kdownloads, 30 days#558 of 619 we track · below the median+2 likes, downloads +36% this week166 likesHugging Face2026-10-24

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

No API provider serves it, so its downloads are people running it themselves: 16 quantized builds and 7 Spaces.

  • As a service0no API provider listed
  • On own hardware16quantized builds
  • Built on1313 fine-tunes · 0 adapters · 0 merges
  • In apps7Hugging Face Spaces

Top Spaces running it: hugging-apps/laya-hebrew ♥ 1

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 16 GB card at INT4

About 0.3 GB at INT4, 0.5 GB at FP8, 1.0 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.3 GB of weights (estimate; KV cache and activations extra)INT40.3 GBFP8: about 0.5 GB of weights (estimate; KV cache and activations extra)FP80.5 GBBF16: about 1.0 GB of weights (estimate; KV cache and activations extra)BF161.0 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.3 GB of weights (estimate; KV cache and activations extra)INT40.3 GBFP8: about 0.5 GB of weights (estimate; KV cache and activations extra)FP80.5 GBBF16: about 1.0 GB of weights (estimate; KV cache and activations extra)BF161.0 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

Weights, every dated article, and repo commits on one rail.

13 repo commits since the weights landed

Teal is the weights (2026-09-18), grey ticks are repo commits.

Oct2026-10-03: 1 repo commit2026-09-24: 3 repo commits2026-09-23: 2 repo commits2026-09-19: 3 repo commits2026-09-18: 4 repo commitsWeights 2026-09-18 · 2026-09-18Weights 2026-09-18now
Oct2026-10-03: 1 repo commit2026-09-24: 3 repo commits2026-09-23: 2 repo commits2026-09-19: 3 repo commits2026-09-18: 4 repo commitsWeights 2026-09-18 · 2026-09-18Weights 2026-09-18now

What people built on it

29 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

29 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

16 quantized (Hugging Face model tree)13 fine-tunes (Hugging Face model tree)16 quantized13 fine-tunes
16 quantized (Hugging Face model tree)13 fine-tunes (Hugging Face model tree)16 quantized13 fine-tunes

All variants →

Reference

Everything else, folded: the full tables, every source.

Benchmarks

15 rows

Benchmarks 15 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (15)No confidence intervals unless the source gave them; settings differ between rows, so compare within a benchmark, not across. Date = the benchmark's own date when it gives one, else when we read it.
BenchmarkValueSetting / notesReported byDate
author-reported Brier0.06—model author2026-10-07
author-reported ECE0.21—model author2026-10-07
author-reported ECE0.19noulmodel author2026-10-07
author-reported ECE0.26choicemodel author2026-10-07
author-reported ECE0.2scoremodel author2026-10-07
author-reported accuracy0.77—model author2026-10-07
author-reported accuracy0.8invoice processingmodel author2026-10-07
author-reported accuracy0.77security incidentsmodel author2026-10-07
author-reported accuracy0.76customer servicemodel author2026-10-07
author-reported accuracy0.73agent-trace observabilitymodel author2026-10-07
author-reported accuracy0.86noulmodel author2026-10-07
author-reported accuracy0.73choicemodel author2026-10-07
author-reported accuracy0.72scoremodel author2026-10-07
author-reported score MAE0.24—model author2026-10-07
author-reported soft acc0.47—model author2026-10-07

Use-case evidence

2 use cases

What it is good at 2 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

17 fields

Listed in Decision models

Facts

Pipeline tagtext-classification
Librarytransformers
ArchitecturesLayaTypedDecisions
Model typelaya
Params by dtypeF16: 421,293,830
Size bandS
MoEno
Languagesen
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: not in registry · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: not in registry · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for laya-typed-decisions: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)1.0 GB · Edge (<4 GB)
FP8 (1 byte/param)0.5 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.3 GB · Edge (<4 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

Decision facts

catalog

Decision-model catalog curated

How it was madefine-tune of Laya on LocalLLaMA/typed-decisions train split (teacher-labelled); ~4-5 h on Kaggle free 2xT4
Lineage bucketF - fine-tune of an open model (public/synthetic data)
Lineage evidencemodel card
Base modelLaya (ModernBERT-large)
Hosted price (input)self-hosted/M
Sourcehttps://huggingface.co/convaiinnovations/laya-typed-decisions

All variants

29 variants

Lineage

Original model Family: convaiinnovations/laya-typed 29 derivatives on the Hub

quantized: 16finetune: 13

Top variants (29 shown, ranked by downloads)

Relation
Quant
29 rows
Variant Relation Quant Params Band License Author Likes Downloads
mys/laya-typed-decisions-GGUF quantized GGUF — — apache-2.0 mys 6 3.5k
fr0stbit3/laya-typed-decisions-gguf quantized gguf — — apache-2.0 fr0stbit3 0 917
onnx-community/laya-typed-decisions-ONNX quantized — — — apache-2.0 onnx-community 0 317
aac6fef/laya-typed-decisions-mlx finetune mlx 421M S apache-2.0 aac6fef 6 0
ti3x-m/laya-typed-decisions-onnx quantized — — — apache-2.0 ti3x-m 1 237
Suarify/laya-typed-decisions-onnx quantized — — — apache-2.0 Suarify 0 195
aac6fef/laya-typed-decisions-coreml quantized — — — apache-2.0 aac6fef 0 162
PythiaFinance/8ball finetune — 421M S apache-2.0 PythiaFinance 2 20
rupeshs/laya-typed-decisions-ov-int8 quantized int8 — — apache-2.0 rupeshs 2 0
NMTZ/laya-typed-decisions-421m-coreml-ane quantized — — — apache-2.0 NMTZ 1 32
ahmedandaloes/laya-typed-decisions-CoreAI quantized — — — — ahmedandaloes 0 79
MissingPackage/jev-d-0.4b-onnx quantized — — — apache-2.0 MissingPackage 1 0
VishalMysore/layaForWebTrained quantized — — — apache-2.0 VishalMysore 1 0
aac6fef/laya-typed-decisions-coreml-adaptive-fp16 quantized -fp16 — — apache-2.0 aac6fef 0 45
daviestechlabs/laya-homelab-router finetune — 421M S apache-2.0 daviestechlabs 0 39
vtava/Laya-1.2-speedup-standalone finetune — 421M S — vtava 0 26
vtava/Laya-1.2-speedup-standalone-fp16 finetune -fp16 421M S — vtava 0 25
aac6fef/laya-typed-decisions-coreml-adaptive-fp32 quantized — — — apache-2.0 aac6fef 0 22
vtava/Laya-1.2-speedup finetune — — — — vtava 0 19
sumitranjan/Jev-Laya-Guard-Lite finetune — 421M S apache-2.0 sumitranjan 0 6
sivasub987/mandate-1-laya finetune — 421M S apache-2.0 sivasub987 0 0
yehor-oleksiuk/laya-typed-decisions-onnx quantized — — — apache-2.0 yehor-oleksiuk 0 0
dnagpt/laya-bio-models finetune — — — other dnagpt 0 0
VishalMysore/layaMOE finetune — — — apache-2.0 VishalMysore 0 0
VishalMysore/laya-moe-web quantized — — — apache-2.0 VishalMysore 0 0
jayzou3773/laya-ra2-v33 finetune — 421M S apache-2.0 jayzou3773 0 0
Dyam/sysone-laya-typed-decisions-onnx quantized — — — apache-2.0 Dyam 0 0
Dipto084/safe_laya finetune — 421M S apache-2.0 Dipto084 0 0
Aquos06/LayaMacro finetune — — — cc-by-nc-sa-4.0 Aquos06 0 0

Repository changelog

13 commits
changed in the last 7 daysOther: 2026-10-24all changes

Repository changelog 13 commits

DateCommitSHA
2026-10-03 chore: root config.json so the Hub tracks downloads e929ae5
2026-09-24 README: laya 0.3.14 release notes and docs site 1a793eb
2026-09-24 README: laya 0.3.13 release notes 92f2b36
2026-09-24 README: laya 0.3.12 release notes 3279c7d
2026-09-23 README: laya 0.3.11 release notes bc76315
2026-09-23 Model card: calibration note and faster loading dd07995
2026-09-19 Add the Laya mark to the card; document Router.preload / Router.attach f9ab0b2
2026-09-19 chore: point encoder at the upstream model id instead of a local build path a398bc6
2026-09-19 docs: measured benchmarks, family hub links, Router usage, honest limits ab82d36
2026-09-18 Update README.md 5ee0035
2026-09-18 Laya fine-tuned on typed-decisions: Accuracy 0.766 (beats Jev 0.727) 843893f
2026-09-18 Laya fine-tuned on typed-decisions: Accuracy 0.766 (beats Jev 0.727) a3f934b
2026-09-18 initial commit b2dde97

Similar models

3 models

Similar models

  • laya · 421M
    same size band (S), same task (text-classification), permissive license
  • lavoir · 422M
    same size band (S), same task (text-classification)
  • GLiNER2.5-Decide · 486M
    same size band (S), same task (text-classification), permissive license

Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:43 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:18 UTC · Last verified 2026-10-25

Follow laya-typed-decisions

Watch this model

Email alerts are not open yet; the feeds above are the same data. See feeds for the item schema.