--- title: "Laya-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/ce86ea17-f8a2-43ac-b4ed-5814f58345c3" updated: "2026-11-13" --- # Laya-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Small 421M-parameter decision model in GGUF form that you serve locally and call through a systemone API. For developers who use llama.cpp tooling and want a compact classifier. Laya-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by ggml-org ## About ### What it is Laya-GGUF is a GGUF conversion of Laya, a small decision model with 421 million parameters, filed under text classification. A conversion tool made the files automatically from the original model. The card is short, so it says little about what the model decides. ### Who it suits Developers who already use llama.cpp tools and want a compact model behind a local server. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Application developers | Run a small decision model beside their app | Start the server and call its systemone API | | Open-source tooling | llama.cpp users | Try a converted model with one command | Serve the model straight from Hugging Face | | Education | Students | Look at how a small converted model is packaged | Compare its size with larger models | Skip it if you need documented labels or outputs, because the card does not describe them. ### Where to use it - The Llama app - A terminal, using the llama command - Any application that can call the model's systemone API on a local server | Use case | Who | What they get back | | --- | --- | --- | | Serve the model locally | Developers | A local server that hosts the model | | Call the decision API | Application authors | Responses from the systemone API the card names | ### How to set it up You need either the Llama app or its terminal command, plus a connection that can pull the model from Hugging Face. No key or account is named. - The Llama app, or the llama command in a terminal - Disk space for a small file, about 211 MB at 4-bit by the record's estimate 1. Install the Llama app or its terminal tool. 2. Run the serve command, which pulls the model from Hugging Face. ```bash llama serve -hf ggml-org/Laya-GGUF ``` If you prefer to fetch the files yourself, use the hub tool. ```bash pip install -U huggingface_hub hf download ggml-org/Laya-GGUF ``` ### How to use it Start the server with the serve command, then send requests to its systemone API. The card says this is a decision model meant for that API, and points to a llama.cpp change for details. ```bash llama serve -hf ggml-org/Laya-GGUF ``` | Tool | What it does | | --- | --- | | llama serve | Starts a local server and loads the model | | -hf | Names the Hugging Face repository to pull the model from | | systemone API | The interface the card says this model is used through | ### Example You start the server with the serve command and send a request to its systemone API. The card shows no sample request or reply, so read the llama.cpp notes it points to for the exact format. ### For newcomers and experts If you are new to this, run the serve command and check that the server starts. That alone confirms the model loads on your machine. If you know the field, you have a 421M-parameter GGUF file of a decision model, about 211 MB at 4-bit by estimate. It is not a chat model. Its request and response schema is documented outside the card. Run the serve command → The model downloads and loads → Send a request to the systemone API → Read the model's decision ### Good to know The files were converted automatically, so training details and limits are not in the card. - License: Apache 2.0 - Cost to run: none named - Data it reaches: files pulled from Hugging Face, plus the requests you send to your own local server - Not for: general chat, since the card calls it a decision model ## README ````markdown # Laya-GGUF Small 421M-parameter decision model in GGUF form that you serve locally and call through a systemone API. For developers who use llama.cpp tooling and want a compact classifier. Made by ggml-org on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Laya-GGUF is a GGUF conversion of Laya, a small decision model with 421 million parameters, filed under text classification. A conversion tool made the files automatically from the original model. The card is short, so it says little about what the model decides. Who it suits: Developers who already use llama.cpp tools and want a compact model behind a local server. ```table Industry | Who uses it | How they use it | Example Software | Application developers | Run a small decision model beside their app | Start the server and call its systemone API Open-source tooling | llama.cpp users | Try a converted model with one command | Serve the model straight from Hugging Face Education | Students | Look at how a small converted model is packaged | Compare its size with larger models ``` Skip it if you need documented labels or outputs, because the card does not describe them. Where to use it: - The Llama app - A terminal, using the llama command - Any application that can call the model's systemone API on a local server ```table Use case | Who | What they get back Serve the model locally | Developers | A local server that hosts the model Call the decision API | Application authors | Responses from the systemone API the card names ``` How to set it up: You need either the Llama app or its terminal command, plus a connection that can pull the model from Hugging Face. No key or account is named. - The Llama app, or the llama command in a terminal - Disk space for a small file, about 211 MB at 4-bit by the record's estimate 1. Install the Llama app or its terminal tool. 2. Run the serve command, which pulls the model from Hugging Face. ```bash llama serve -hf ggml-org/Laya-GGUF ``` If you prefer to fetch the files yourself, use the hub tool. ```bash pip install -U huggingface_hub hf download ggml-org/Laya-GGUF ``` How to use it: Start the server with the serve command, then send requests to its systemone API. The card says this is a decision model meant for that API, and points to a llama.cpp change for details. ```bash llama serve -hf ggml-org/Laya-GGUF ``` ```table Tool | What it does llama serve | Starts a local server and loads the model -hf | Names the Hugging Face repository to pull the model from systemone API | The interface the card says this model is used through ``` Example: You start the server with the serve command and send a request to its systemone API. The card shows no sample request or reply, so read the llama.cpp notes it points to for the exact format. For newcomers and experts: If you are new to this, run the serve command and check that the server starts. That alone confirms the model loads on your machine. If you know the field, you have a 421M-parameter GGUF file of a decision model, about 211 MB at 4-bit by estimate. It is not a chat model. Its request and response schema is documented outside the card. ```flow Run the serve command The model downloads and loads Send a request to the systemone API Read the model's decision ``` Good to know: The files were converted automatically, so training details and limits are not in the card. - License: Apache 2.0 - Cost to run: none named - Data it reaches: files pulled from Hugging Face, plus the requests you send to your own local server - Not for: general chat, since the card calls it a decision model ## On Hugging Face, 13 November 2026 - Task: text classification - Parameters: 421M - Weights: about 211 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 16,039 - Likes: 41 - License: apache-2.0 - Based on: convaiinnovations/laya - Quantized versions: 1 - Tags: gguf, quantized, decision-model, text-classification, feature-extraction ## Links - Model: https://huggingface.co/ggml-org/Laya-GGUF - Files: https://huggingface.co/ggml-org/Laya-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download ggml-org/Laya-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [ggml-org/Laya-GGUF on Hugging Face](https://huggingface.co/ggml-org/Laya-GGUF) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Laya-GGUF (this page) | 16,039 | 41 | 421M | apache-2.0 | 2026-11-12 | | [Kev-4B by ggml-org](https://mindket.com/p/e2e01d00-d647-46fb-89a3-48661fa412ac) | 39,531 | 34 | 4.2B | apache-2.0 | 2026-10-19 | | [MiniCPM-OCR Jev GGUF](https://mindket.com/p/925e0e80-eaca-47f8-8edc-b26e2ba06f7c) | 31,316 | 22 | 1.9B | apache-2.0 | 2026-11-02 | | [EmbeddingGemma 2 Typed Decisions](https://mindket.com/p/e111b50b-6324-42e6-885a-175f766e065e) | 1,800 | 89 | 272M | apache-2.0 | 2026-11-04 | | [Mica v0.1 4B](https://mindket.com/p/55daa34c-73de-47b6-a176-900851a69bf1) | 3,436 | 52 | 4.2B | apache-2.0 | 2026-09-28 | | [jevos-v4](https://mindket.com/p/cb6031a9-f6ec-4eb2-b36a-0543673bb7d9) | 1,475 | 22 | 882M | mit | 2026-10-09 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · derefr · 2026-10-15](https://news.ycombinator.com/item?id=50107469): We’re releasing Jev 1.14.0 along with experimental features for dreamers: \> Setting up local decision / classification models is as easy as telling the agent you already use "set up laya on llama cpp locally https://github.com/ggml-org/llama.cpp https://huggingface.co/ggml-org/Laya-GGUF" (or your inference engine and model of choice, walk away for a minutes, and come… - [Hacker News · Zambyte · 2026-10-15](https://news.ycombinator.com/item?id=50103009): We’re releasing Jev 1.14.0 along with experimental features for dreamers: The extra funny thing about this is that the target audience is people who use agentic AI systems (system one thinking as a compliment to system two thinking). Setting up local decision / classification models is as easy as telling the agent you already use "set up laya on llama cpp locally… ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-12 - First published: 2026-10-01 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ggml-org/Laya-GGUF on Hugging Face](https://huggingface.co/ggml-org/Laya-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/ce86ea17-f8a2-43ac-b4ed-5814f58345c3) - [Its page on Mindket](https://mindket.com/p/ce86ea17-f8a2-43ac-b4ed-5814f58345c3)