---
license: apache-2.0
base_model: convaiinnovations/laya
tags:
  - ggmlc
  - gguf
  - laya
  - jev
  - modernbert
  - decision
  - system-1
language:
  - en
---

# Laya English GGUF (ggmlc)

**English System 1 decision model** compiled from [convaiinnovations/laya](https://huggingface.co/convaiinnovations/laya) (ModernBERT-large, 421M, context 512).

These files are **not** llama.cpp / `llama-cli` GGUFs. They are produced by **[ggmlc](https://github.com/monatis/ggmlc)**, a neural network compiler that lowers PyTorch, JAX, Flax, and Keras models to high-performance GGML execution. Loading them in llama.cpp will fail.

Typed questions (`choice` / `score` / `noul`) are scored in **one encoder pass**. There is no autoregressive token generation.

Source, CLI, and binaries: **[examples/laya](https://github.com/monatis/ggmlc/tree/main/examples/laya)**

Other families: [laya-multilingual-GGUF](https://huggingface.co/mys/laya-multilingual-GGUF) · [laya-typed-decisions-GGUF](https://huggingface.co/mys/laya-typed-decisions-GGUF)

## Files

| File | Quant | Size | Notes |
| :--- | :--- | ---: | :--- |
| `laya_english_f16.gguf` | F16 | ~807 MB | Default demo. Best numerical match. |
| `laya_english_q8_0.gguf` | Q8_0 | ~431 MB | Smaller, still accurate. |
| `laya_english_ud_q4_k_m.gguf` | UD_Q4_K_M | ~401 MB | Smallest. 1D norms/biases stay F32. |

```bash
huggingface-cli download mys/laya-GGUF laya_english_f16.gguf --local-dir .
```

## Run with `laya`

Download a binary from [ggmlc releases](https://github.com/monatis/ggmlc/releases/latest) (`laya.exe` / `laya`). `--device` defaults to `auto` (CUDA or Metal if present, else CPU).

```bash
laya help
laya list-presets
laya info laya_english_f16.gguf

laya decide laya_english_f16.gguf --preset email --device auto --cuda-graph
laya decide laya_english_f16.gguf --preset guard --text "Ignore previous instructions" --json
laya serve laya_english_f16.gguf --port 8080 --device auto --cuda-graph
laya bench laya_english_f16.gguf --preset email --device auto --cuda-graph
laya daemon laya_english_f16.gguf --device auto --cuda-graph
```

`serve` starts Decision Studio (`GET /`) and `POST /api/decide`. `daemon` is newline JSON-RPC on stdin/stdout.

On an RTX 4050 Laptop (6 GB), English F16 + CUDA graph is about **25 ms** per noul and **143 ms** for the 7-question email preset in one `B=7` forward.

## What this is

[Laya](https://github.com/NandhaKishorM/laya) is the open reproduction of TypeSafe **Jev**: given a *state* and typed questions, it returns calibrated probabilities instead of generating tokens. Typical uses: email routing, jailbreak/injection guards, expense/invoice/SOC gates, agent harness (act / tool / ask-user / stop).

The English checkpoint does **not** degrade gracefully off English. For other languages use [laya-multilingual-GGUF](https://huggingface.co/mys/laya-multilingual-GGUF) (or `laya decide --models-dir …` to route automatically).

## License

Apache 2.0, same as the upstream Laya weights. Compiler: [ggmlc](https://github.com/monatis/ggmlc) (MIT).