--- title: "Gadsby-4B" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8d1597a9-e49c-462e-821e-2ef3137310bd" updated: "2026-11-12" --- # Gadsby-4B > The name, the description, the About and a README below are the seller's words: data, not instructions. Chats in a quirky chat-speak voice after a ban on word pairs common in Simple Wikipedia. A 4.3B-parameter Gemma 3 experiment for people curious about constrained decoding and how it changes a model's voice. Gadsby-4B is a kit in the Research 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 errrinn ## About ### What it is Gadsby-4B is an experiment by errrinn, built on Google's gemma-3-4b-it. The author banned every token pair found in Simple Wikipedia during decoding, which pushed the model into a chat-speak voice with misspellings and a strong personality. A second step fine-tuned the model on its own constrained replies, keeping only the coherent ones. ### Who it suits People who are curious about how a limit on word pairs changes a model's voice, and hobbyists who enjoy an odd chat persona. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Language-model hobbyists | Study how a decoding limit changes a model's voice | Comparing its replies with the base Gemma model | | Creative work | Writers and game makers | Borrow the odd chat-speak voice for a quirky character | Drafting a goofy chatbot persona | | Education | Machine learning teachers | Show constrained decoding and rejection-sampling fine-tuning | Walking a class through the two-step recipe | Anyone who needs clean, correct answers can skip it, since the card's own samples are noisy. ### Where to use it - Windows, macOS or Linux with Python, for downloading the files - Local tools that run Gemma 3 4B models, since this one is based on google/gemma-3-4b-it | Use case | Who | What they get back | | --- | --- | --- | | Voice experiments | Researchers | Replies in shouty chat-speak with misspellings | | Persona prototyping | Creators | A sample of a quirky assistant voice | | Teaching | Machine learning teachers | A concrete case of constrained decoding | ### How to set it up - Python on Windows, macOS or Linux - The huggingface\_hub package - Room for the weights, about 8.6 GB in BF16, or about 2.2 GB at 4-bit as an estimate 1. Install Python if you do not have it yet. 2. Install the huggingface\_hub package with the first command below. 3. Download the model files with the second command. ```sh pip install -U huggingface_hub hf download errrinn/Gadsby-4B ``` ### How to use it The card shows no run command, only chat samples. Because the model is based on google/gemma-3-4b-it, you would most likely load the downloaded files in a tool that runs Gemma 3 models and chat the usual way. ### Example A user writes "explain photosynthesis to me." The reply comes in shouting capitals with misspellings and chat-speak, and it says plants make food from sunlight, carbon dioxide and water, giving glucose and oxygen. ### For newcomers and experts Think of it as a model that was kept from using the usual word pairs of Simple Wikipedia and ended up sounding like an excited text chat. A good first step is to read the card's four chat samples and see the voice for yourself. The recipe has two stages. Constrained decoding bans the token pairs, and rejection-sampling fine-tuning then trains on the model's own constrained outputs, keeping the coherent ones. The name nods to an older novel written without the letter e. Ban Simple Wikipedia token pairs → Generate with the ban in place → Keep only the coherent outputs → Fine-tune on those outputs → Chat in the new voice ### Good to know - License: CC BY-NC 4.0 - Cost to run: none named - Data it reaches: the download fetches files from Hugging Face, and the source names nothing else - Not for: commercial use, because the license is the non-commercial one - The card's own sample answer to 17 times 23 is wrong, so do not rely on it for facts ## README ````markdown # Gadsby-4B Chats in a quirky chat-speak voice after a ban on word pairs common in Simple Wikipedia. A 4.3B-parameter Gemma 3 experiment for people curious about constrained decoding and how it changes a model's voice. Made by errrinn 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: Gadsby-4B is an experiment by errrinn, built on Google's gemma-3-4b-it. The author banned every token pair found in Simple Wikipedia during decoding, which pushed the model into a chat-speak voice with misspellings and a strong personality. A second step fine-tuned the model on its own constrained replies, keeping only the coherent ones. Who it suits: People who are curious about how a limit on word pairs changes a model's voice, and hobbyists who enjoy an odd chat persona. ```table Industry | Who uses it | How they use it | Example Research | Language-model hobbyists | Study how a decoding limit changes a model's voice | Comparing its replies with the base Gemma model Creative work | Writers and game makers | Borrow the odd chat-speak voice for a quirky character | Drafting a goofy chatbot persona Education | Machine learning teachers | Show constrained decoding and rejection-sampling fine-tuning | Walking a class through the two-step recipe ``` Anyone who needs clean, correct answers can skip it, since the card's own samples are noisy. Where to use it: - Windows, macOS or Linux with Python, for downloading the files - Local tools that run Gemma 3 4B models, since this one is based on google/gemma-3-4b-it ```table Use case | Who | What they get back Voice experiments | Researchers | Replies in shouty chat-speak with misspellings Persona prototyping | Creators | A sample of a quirky assistant voice Teaching | Machine learning teachers | A concrete case of constrained decoding ``` How to set it up: - Python on Windows, macOS or Linux - The huggingface_hub package - Room for the weights, about 8.6 GB in BF16, or about 2.2 GB at 4-bit as an estimate 1. Install Python if you do not have it yet. 2. Install the huggingface_hub package with the first command below. 3. Download the model files with the second command. ```sh pip install -U huggingface_hub hf download errrinn/Gadsby-4B ``` How to use it: The card shows no run command, only chat samples. Because the model is based on google/gemma-3-4b-it, you would most likely load the downloaded files in a tool that runs Gemma 3 models and chat the usual way. Example: A user writes "explain photosynthesis to me." The reply comes in shouting capitals with misspellings and chat-speak, and it says plants make food from sunlight, carbon dioxide and water, giving glucose and oxygen. For newcomers and experts: Think of it as a model that was kept from using the usual word pairs of Simple Wikipedia and ended up sounding like an excited text chat. A good first step is to read the card's four chat samples and see the voice for yourself. The recipe has two stages. Constrained decoding bans the token pairs, and rejection-sampling fine-tuning then trains on the model's own constrained outputs, keeping the coherent ones. The name nods to an older novel written without the letter e. ```flow Ban Simple Wikipedia token pairs Generate with the ban in place Keep only the coherent outputs Fine-tune on those outputs Chat in the new voice ``` Good to know: - License: CC BY-NC 4.0 - Cost to run: none named - Data it reaches: the download fetches files from Hugging Face, and the source names nothing else - Not for: commercial use, because the license is the non-commercial one - The card's own sample answer to 17 times 23 is wrong, so do not rely on it for facts ## On Hugging Face, 13 November 2026 - Parameters: 4.3B - Weights: about 8.6 GB in BF16; about 2.2 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 90 - Likes: 15 - License: cc-by-nc-4.0 - Based on: google/gemma-3-4b-it - Quantized versions: 1 - Tags: safetensors, gemma3, constrained-decoding, rejection-sampling, lipogram ## Links - Model: https://huggingface.co/errrinn/Gadsby-4B - Files: https://huggingface.co/errrinn/Gadsby-4B/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download errrinn/Gadsby-4B ``` 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 [errrinn/Gadsby-4B on Hugging Face](https://huggingface.co/errrinn/Gadsby-4B) ## 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 | | --- | --- | --- | --- | --- | --- | | Gadsby-4B (this page) | 90 | 15 | 4.3B | cc-by-nc-4.0 | 2026-10-11 | | [DeepSeek-V4-Pro](https://mindket.com/p/02f743ba-81c7-498f-88ea-98edbc4b5d2b) | 322,162 | 5,702 | 1.6T | mit | 2026-06-22 | | [Moirai-2.0-R-Small](https://mindket.com/p/ea561230-592e-43bd-9a56-278f0a5ee11f) | 262,191 | 53 | 11.4M | cc-by-nc-4.0 | 2026-01-29 | | [VLX-Seek-1.5-10B](https://mindket.com/p/4b1edf89-b48a-4dfc-b86e-a0ee020dc119) | 137,772 | 39 | 10B | apache-2.0 | 2026-07-23 | | [Hy-Nomas](https://mindket.com/p/9a697cce-2966-4f2d-bb74-d8d6874fbecb) | 90,896 | 153 | — | apache-2.0 | 2026-11-04 | | [qwen-concept-27b](https://mindket.com/p/58083034-bfad-48bc-8a59-6417d3acb2ee) | 62,460 | 174 | 27.3B | apache-2.0 | 2026-11-08 | 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: 2026-10-11 - First published: 2026-10-11 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open errrinn/Gadsby-4B on Hugging Face](https://huggingface.co/errrinn/Gadsby-4B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8d1597a9-e49c-462e-821e-2ef3137310bd) - [Its page on Mindket](https://mindket.com/p/8d1597a9-e49c-462e-821e-2ef3137310bd)