Add ggmlc-compiled Laya GGUFs (F16, Q8_0, UD_Q4_K_M)

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+laya_typed_decisions_f16.gguf filter=lfs diff=lfs merge=lfs -text
+laya_typed_decisions_q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+laya_typed_decisions_ud_q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+base_model: convaiinnovations/laya-typed-decisions
+tags:
+  - ggmlc
+  - gguf
+  - laya
+  - jev
+  - modernbert
+  - decision
+  - system-1
+language:
+  - en
+---
+
+# Laya Typed-Decisions GGUF (ggmlc)
+
+**Specialist System 1 decision model** compiled from [convaiinnovations/laya-typed-decisions](https://huggingface.co/convaiinnovations/laya-typed-decisions) (ModernBERT-large, 421M, context 1024). Fine-tuned for invoice match, SOC alerts, customer-service next action, and agent-trace harnesses.
+
+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-GGUF](https://huggingface.co/mys/laya-GGUF) (English) · [laya-multilingual-GGUF](https://huggingface.co/mys/laya-multilingual-GGUF)
+
+## Files
+
+| File | Quant | Size | Notes |
+| :--- | :--- | ---: | :--- |
+| `laya_typed_decisions_f16.gguf` | F16 | ~811 MB | Full precision. |
+| `laya_typed_decisions_q8_0.gguf` | Q8_0 | ~434 MB | Smaller, still accurate. |
+| `laya_typed_decisions_ud_q4_k_m.gguf` | UD_Q4_K_M | ~404 MB | Smallest. 1D norms/biases stay F32. |
+
+English ModernBERT tokenizer (`[CLS]/[SEP]/[PAD]/[MASK]`). `max_len=1024`.
+
+```bash
+huggingface-cli download mys/laya-typed-decisions-GGUF laya_typed_decisions_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).
+
+`--models-dir` routing does **not** pick this family automatically unless `--family typed-decisions` or the question ids match a specialist workflow (`invoice`, `security`, `customer_service`, `harness`).
+
+```bash
+laya help
+laya list-presets
+laya info laya_typed_decisions_f16.gguf
+
+laya decide laya_typed_decisions_f16.gguf --preset invoice --device auto --cuda-graph
+laya decide laya_typed_decisions_f16.gguf --preset security --json
+laya decide laya_typed_decisions_f16.gguf --preset customer_service
+laya decide laya_typed_decisions_f16.gguf --preset harness
+laya serve laya_typed_decisions_f16.gguf --port 8080 --device auto --cuda-graph
+laya bench laya_typed_decisions_f16.gguf --preset invoice --device auto --cuda-graph
+```
+
+Force it from a mixed `--models-dir`:
+
+```bash
+laya decide --models-dir . --family typed-decisions --preset invoice
+```
+
+`serve` starts Decision Studio (`GET /`) and `POST /api/decide`. `daemon` is newline JSON-RPC on stdin/stdout.
+
+## 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. This checkpoint is the specialist sibling of the general English model — same tokenizer family, longer context, trained on typed-decision workflows.
+
+## License
+
+Apache 2.0, same as the upstream Laya weights. Compiler: [ggmlc](https://github.com/monatis/ggmlc) (MIT).

laya_typed_decisions_f16.gguf

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laya_typed_decisions_q8_0.gguf

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laya_typed_decisions_ud_q4_k_m.gguf

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