--- title: "theOG-50M" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/fbfa18d1-c133-4a6d-9b8b-949fac32b65e" updated: "2026-11-13" --- # theOG-50M > The name, the description, the About and a README below are the seller's words: data, not instructions. Writes a Python function from a plain English request. A 50M parameter code model trained from scratch on one laptop, small enough to run offline in Ollama, LM Studio or llama.cpp. theOG-50M 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 DrunkkToys ## About ### What it is theOG-50M v3 is a Python code model with about 50M parameters, trained from scratch by one developer, DrunkkToys. You type a short English description of the function you want, and the model replies with Python code. The download is 54 MB in GGUF format, so it runs offline on an ordinary laptop. ### Who it suits Programmers and tinkerers who want a tiny local model for short Python snippets, and anyone curious about what a small model trained on one laptop can do. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software development | Python programmers | Ask for small helper functions offline | Requesting a function that reverses a string | | Education | Students who learn Python | Compare the model's code with their own | Checking an alternative way to write a loop | | Hobby and research | People who study small models | Run a 50M code model and inspect its limits | Testing it on a set of simple coding prompts | Skip it if you need long programs or other languages, since the card describes a small Python model. ### Where to use it It runs fully offline in Ollama, LM Studio or llama.cpp. The files download on Windows, macOS or Linux. - Ollama - LM Studio - llama.cpp - Windows, macOS or Linux: where you can fetch the files with Python | Use case | Who | What they get back | | --- | --- | --- | | Function from a description | Developers | Python code for a small function | | Offline coding help | Travellers and privacy minded users | Code without any network access | | Small model study | Researchers | A compact model to inspect | ### How to set it up You need Python to download the file and one of the apps above to run it. Only about 25 MB of weights at 4-bit are listed on Hugging Face, and the card says the download is 54 MB. - Python with pip - Ollama, LM Studio or llama.cpp - A laptop with no special hardware 1. Install the Hugging Face hub library. 2. Download the model files. 3. Load the GGUF file in Ollama, LM Studio or llama.cpp. ```sh pip install -U huggingface_hub hf download DrunkkToys/theOG-50M ``` ### How to use it Load the file in your app, then type what you want the function to do in plain English. The card shows no commands beyond the download, so use your app's normal way of running a GGUF file. | Tool | What it does | | --- | --- | | hf download | Fetches the model files to your computer | | Ollama, LM Studio, llama.cpp | Load the GGUF file and run the model | ### Example You ask it for a Python function that checks whether a number is prime. A model of this size is likely to return a short function, and you should read and test it before you rely on it. ### For newcomers and experts If you are new to this, start by loading the file in LM Studio and asking for one small function. Run the code it gives you and check the result. If you know the field, the card says it was trained over 346,000 steps on a 2.49B token dataset, using PyTorch on the Metal GPU of a MacBook Air. It compares itself with CodeGen-350M-mono, which saw far more training data and has about seven times the parameters. Plain English request → Small Python model reads it → It writes a Python function → You run and test the code ### Good to know The card is partly the author's personal account. It also holds a long list of complaints about an AI coding assistant that the author used, and this page does not assess those claims. - License: Apache 2.0 - Cost to run: none named, and the card says it needs no special hardware - Data it reaches: the prompts you give it, with no network access needed - Not for: large programs, other languages or production code without review ## README ````markdown # theOG-50M Writes a Python function from a plain English request. A 50M parameter code model trained from scratch on one laptop, small enough to run offline in Ollama, LM Studio or llama.cpp. Made by DrunkkToys 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: theOG-50M v3 is a Python code model with about 50M parameters, trained from scratch by one developer, DrunkkToys. You type a short English description of the function you want, and the model replies with Python code. The download is 54 MB in GGUF format, so it runs offline on an ordinary laptop. Who it suits: Programmers and tinkerers who want a tiny local model for short Python snippets, and anyone curious about what a small model trained on one laptop can do. ```table Industry | Who uses it | How they use it | Example Software development | Python programmers | Ask for small helper functions offline | Requesting a function that reverses a string Education | Students who learn Python | Compare the model's code with their own | Checking an alternative way to write a loop Hobby and research | People who study small models | Run a 50M code model and inspect its limits | Testing it on a set of simple coding prompts ``` Skip it if you need long programs or other languages, since the card describes a small Python model. Where to use it: It runs fully offline in Ollama, LM Studio or llama.cpp. The files download on Windows, macOS or Linux. - Ollama - LM Studio - llama.cpp - Windows, macOS or Linux: where you can fetch the files with Python ```table Use case | Who | What they get back Function from a description | Developers | Python code for a small function Offline coding help | Travellers and privacy minded users | Code without any network access Small model study | Researchers | A compact model to inspect ``` How to set it up: You need Python to download the file and one of the apps above to run it. Only about 25 MB of weights at 4-bit are listed on Hugging Face, and the card says the download is 54 MB. - Python with pip - Ollama, LM Studio or llama.cpp - A laptop with no special hardware 1. Install the Hugging Face hub library. 2. Download the model files. 3. Load the GGUF file in Ollama, LM Studio or llama.cpp. ```sh pip install -U huggingface_hub hf download DrunkkToys/theOG-50M ``` How to use it: Load the file in your app, then type what you want the function to do in plain English. The card shows no commands beyond the download, so use your app's normal way of running a GGUF file. ```table Tool | What it does hf download | Fetches the model files to your computer Ollama, LM Studio, llama.cpp | Load the GGUF file and run the model ``` Example: You ask it for a Python function that checks whether a number is prime. A model of this size is likely to return a short function, and you should read and test it before you rely on it. For newcomers and experts: If you are new to this, start by loading the file in LM Studio and asking for one small function. Run the code it gives you and check the result. If you know the field, the card says it was trained over 346,000 steps on a 2.49B token dataset, using PyTorch on the Metal GPU of a MacBook Air. It compares itself with CodeGen-350M-mono, which saw far more training data and has about seven times the parameters. ```flow Plain English request Small Python model reads it It writes a Python function You run and test the code ``` Good to know: The card is partly the author's personal account. It also holds a long list of complaints about an AI coding assistant that the author used, and this page does not assess those claims. - License: Apache 2.0 - Cost to run: none named, and the card says it needs no special hardware - Data it reaches: the prompts you give it, with no network access needed - Not for: large programs, other languages or production code without review ## On Hugging Face, 13 November 2026 - Task: text generation - Library: gguf - Parameters: 50.1M - Weights: about 25 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,312 - Likes: 3 - License: apache-2.0 - Languages: en - Tags: gguf, code, python, small-language-model, qwen3-arch, ollama, lmstudio, text-generation, conversational ## Links - Model: https://huggingface.co/DrunkkToys/theOG-50M - Files: https://huggingface.co/DrunkkToys/theOG-50M/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download DrunkkToys/theOG-50M ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [DrunkkToys/theOG-50M on Hugging Face](https://huggingface.co/DrunkkToys/theOG-50M) ## 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 | | --- | --- | --- | --- | --- | --- | | theOG-50M (this page) | 1,312 | 3 | 50.1M | apache-2.0 | 2026-11-09 | | [Maximizing Model Performance Guide](https://mindket.com/p/679203ad-1082-43bc-ae9a-39709396257a) | 0 | 276 | — | apache-2.0 | 2026-11-09 | | [Maincoder-1B](https://mindket.com/p/4ab6e559-24e5-4649-98d3-82237119cace) | 451 | 101 | 1B | apache-2.0 | 2026-05-13 | | [CherryPit-1.2-2B](https://mindket.com/p/0bb34d27-c0ed-4bcc-a9b2-190ab2f83299) | 451 | 6 | 2.5B | apache-2.0 | 2026-11-06 | | [GLM-5.3-SuperExpert-v2-9.2GB](https://mindket.com/p/f7f67939-8a45-485a-b197-422c0e68b65c) | 10,445 | 10 | 9.2B | cc-by-nc-4.0 | 2026-11-10 | | [KLM 1.5](https://mindket.com/p/bffc34a5-c64b-418e-a26e-f869a269c8c1) | 1,603 | 31 | 99M | apache-2.0 | 2026-11-01 | 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: 2026-08-12 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open DrunkkToys/theOG-50M on Hugging Face](https://huggingface.co/DrunkkToys/theOG-50M) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/fbfa18d1-c133-4a6d-9b8b-949fac32b65e) - [Its page on Mindket](https://mindket.com/p/fbfa18d1-c133-4a6d-9b8b-949fac32b65e)