--- title: "KLM 1.6" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8b218890-16d1-4ff9-b98e-3eea5e8533e8" updated: "2026-11-12" --- # KLM 1.6 > The name, the description, the About and a README below are the seller's words: data, not instructions. Continues English text with a tiny 99M base language model from MinimaLabs. For researchers and hobbyists who want a small model to study, test or fine-tune. KLM 1.6 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by MinimaLabs ## About ### What it is KLM 1.6 is a base language model with 99M parameters from MinimaLabs. It carries on training from a KLM 1.5 checkpoint saved before that model's decay stage. The main change from 1.5 is a longer decay of the learning rate. ### Who it suits It suits researchers and hobbyists who want a tiny English model to study, compare or build on. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Small-model researchers | Compare tiny models on shared benchmarks | A check against SmolLM2-135M on ARC and PIQA | | Software | Developers | Try a text model with a tiny memory footprint | A prototype that loads a 99M model locally | | Education | Students | Study how a small model is trained in stages | A class project on warm-up and decay | People who want a chat assistant can skip it, since this is a base model and not one tuned to follow instructions. ### Where to use it - Hugging Face Transformers, the library the card lists - Windows, macOS or Linux, where you download the files with Python - Machines with little memory, since the weights are about 396 MB in F32 or about 49 MB at 4-bit by estimate | Use case | Who | What they get back | | --- | --- | --- | | Text continuation | Developers | English text that carries on from your prompt | | Benchmark comparison | Researchers | Scores on ARC, HellaSwag, PIQA and ArithMark-3 | | Fine-tuning base | Hobbyists | A small starting point for your own training | ### How to set it up You need these first: - Python and the huggingface\_hub package - The transformers library, since the card lists it - A computer with a few hundred MB of free memory 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Load the model with transformers. ```sh pip install -U huggingface_hub hf download MinimaLabs/KLM-1.6 ``` ### How to use it Load the model in transformers and give it the start of a sentence or paragraph in English. A base model carries the text on rather than answering like an assistant, so write prompts as text to be continued. ### Example You give it the opening of a short paragraph on a simple topic. It writes a few more sentences in the same style. A model this small can drift or repeat, so treat the output as a test, not a finished text. ### For newcomers and experts A base model has learned from lots of text to predict what comes next. A first small thing to try is giving it half a sentence and reading how it finishes. For experts, the model has 24 layers that mix Gated DeltaNet-2 and attention in a 3 to 1 ratio, a hidden size of 512 and a context of 2,048 tokens. It also holds an n-gram memory of 125,000 bigrams and 38,000 trigrams, and its vocabulary holds only 4,100 tokens. Training ran in three stages, a superposition warm-up, a stable stage and a decay. On the Open SLM leaderboard the card reports an Intelligence Index of 33.95, first among models under 100M, 150M and 250M parameters. Warm up with token superposition training → Train steadily at a constant learning rate → Decay the learning rate over 100B tokens → Load the result and continue your text ### Good to know ArithMark-3 score | Label | Value | | --- | --- | | KLM 1.6 | 55.90% | | GPT-X3-150M | 50.90% | | KLM 1.5 | 48.20% | | SmolLM2-135M | 39.20% | - Size: 99M parameters in Safetensors format - Language: English - Context: 2,048 tokens - License: apache-2.0 - Cost to run: none named, no API key or account - Data it reaches: it downloads model files from Hugging Face and works on the text you give it - Not for: none named in the card text shown ## README ````markdown # KLM 1.6 Continues English text with a tiny 99M base language model from MinimaLabs. For researchers and hobbyists who want a small model to study, test or fine-tune. Made by MinimaLabs 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: KLM 1.6 is a base language model with 99M parameters from MinimaLabs. It carries on training from a KLM 1.5 checkpoint saved before that model's decay stage. The main change from 1.5 is a longer decay of the learning rate. Who it suits: It suits researchers and hobbyists who want a tiny English model to study, compare or build on. ```table Industry | Who uses it | How they use it | Example Research | Small-model researchers | Compare tiny models on shared benchmarks | A check against SmolLM2-135M on ARC and PIQA Software | Developers | Try a text model with a tiny memory footprint | A prototype that loads a 99M model locally Education | Students | Study how a small model is trained in stages | A class project on warm-up and decay ``` People who want a chat assistant can skip it, since this is a base model and not one tuned to follow instructions. Where to use it: - Hugging Face Transformers, the library the card lists - Windows, macOS or Linux, where you download the files with Python - Machines with little memory, since the weights are about 396 MB in F32 or about 49 MB at 4-bit by estimate ```table Use case | Who | What they get back Text continuation | Developers | English text that carries on from your prompt Benchmark comparison | Researchers | Scores on ARC, HellaSwag, PIQA and ArithMark-3 Fine-tuning base | Hobbyists | A small starting point for your own training ``` How to set it up: You need these first: - Python and the huggingface_hub package - The transformers library, since the card lists it - A computer with a few hundred MB of free memory 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Load the model with transformers. ```sh pip install -U huggingface_hub hf download MinimaLabs/KLM-1.6 ``` How to use it: Load the model in transformers and give it the start of a sentence or paragraph in English. A base model carries the text on rather than answering like an assistant, so write prompts as text to be continued. Example: You give it the opening of a short paragraph on a simple topic. It writes a few more sentences in the same style. A model this small can drift or repeat, so treat the output as a test, not a finished text. For newcomers and experts: A base model has learned from lots of text to predict what comes next. A first small thing to try is giving it half a sentence and reading how it finishes. For experts, the model has 24 layers that mix Gated DeltaNet-2 and attention in a 3 to 1 ratio, a hidden size of 512 and a context of 2,048 tokens. It also holds an n-gram memory of 125,000 bigrams and 38,000 trigrams, and its vocabulary holds only 4,100 tokens. Training ran in three stages, a superposition warm-up, a stable stage and a decay. On the Open SLM leaderboard the card reports an Intelligence Index of 33.95, first among models under 100M, 150M and 250M parameters. ```flow Warm up with token superposition training Train steadily at a constant learning rate Decay the learning rate over 100B tokens Load the result and continue your text ``` Good to know: ```chart Title: ArithMark-3 score KLM 1.6: 55.90% GPT-X3-150M: 50.90% KLM 1.5: 48.20% SmolLM2-135M: 39.20% ``` - Size: 99M parameters in Safetensors format - Language: English - Context: 2,048 tokens - License: apache-2.0 - Cost to run: none named, no API key or account - Data it reaches: it downloads model files from Hugging Face and works on the text you give it - Not for: none named in the card text shown ## On Hugging Face, 13 November 2026 - Task: text generation - Library: transformers - Parameters: 99M - Weights: about 396 MB in F32; about 49 MB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 909 - Likes: 60 - License: apache-2.0 - Languages: en - Tags: transformers, safetensors, text-generation, small-language-model, base, pretrained, hybrid, gated-deltanet ## Links - Model: https://huggingface.co/MinimaLabs/KLM-1.6 - Files: https://huggingface.co/MinimaLabs/KLM-1.6/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download MinimaLabs/KLM-1.6 ``` 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 [MinimaLabs/KLM-1.6 on Hugging Face](https://huggingface.co/MinimaLabs/KLM-1.6) ## 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 | | --- | --- | --- | --- | --- | --- | | KLM 1.6 (this page) | 909 | 60 | 99M | apache-2.0 | 2026-11-09 | | [KLM 1.5](https://mindket.com/p/bffc34a5-c64b-418e-a26e-f869a269c8c1) | 1,603 | 31 | 99M | apache-2.0 | 2026-11-01 | | [GPT-X3-150M](https://mindket.com/p/36e26f24-6570-49bc-9611-515f3e31cfe9) | 3,000 | 104 | 149M | apache-2.0 | 2026-10-25 | | [Mistral-7B-v0.1](https://mindket.com/p/462400f3-8981-464a-82c5-3c31376c9d1d) | 441,952 | 4,231 | 7.2B | apache-2.0 | 2025-07-24 | | [ARLoop-0.6B](https://mindket.com/p/457fa82c-e2a1-4587-93ed-5435177b083f) | 2,164 | 5 | 583M | apache-2.0 | 2026-11-05 | | [CherryPit-1.2-2B](https://mindket.com/p/0bb34d27-c0ed-4bcc-a9b2-190ab2f83299) | 451 | 6 | 2.5B | apache-2.0 | 2026-11-06 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-11-09 - First published: 2026-11-09 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open MinimaLabs/KLM-1.6 on Hugging Face](https://huggingface.co/MinimaLabs/KLM-1.6) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8b218890-16d1-4ff9-b98e-3eea5e8533e8) - [Its page on Mindket](https://mindket.com/p/8b218890-16d1-4ff9-b98e-3eea5e8533e8)