--- title: "Gpt2 Multiplication Predictor" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8c0b7e1e-7ac7-4413-9ac0-a40d112b26e7" updated: "2026-11-12" --- # Gpt2 Multiplication Predictor > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo that compares GPT-2 models trained to multiply large numbers, including variants named for no reasoning steps and for reasoning steps hidden or written out. For AI researchers and curious learners. Gpt2 Multiplication Predictor 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 yuntian-deng ## About ### What it is This Space is a demo of GPT-2 models that predict the result of multiplying two numbers. It names three models. One uses no chain of thought, one uses an implicit chain of thought for 20 digits, and one uses an explicit chain of thought for 20 digits. The README is only a configuration pointer, so the descriptions here come from the model names. ### Who it suits AI researchers, students and curious people who want to see how small language models handle arithmetic with and without written-out steps. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | AI research | Researchers | Compare reasoning styles on long multiplication | Run the same product through each model | | Education | Students | See where a small model fails at arithmetic | Try a large multiplication and compare answers | | AI development | Developers | Study a small Gradio demo with three models | Read app.py and the tests folder | People who need a dependable calculator can skip it, since the point is to study the models. ### Where to use it - A browser: the Space runs on Hugging Face with nothing to install - Windows, macOS or Linux: run a copy of the Space with Python | Use case | Who | What they get back | | --- | --- | --- | | Compare models | Researchers | Predicted products from the three GPT-2 variants | | Test limits | Students | A look at where each variant gets a product wrong | | Read the code | Developers | A short Gradio app with a tests folder | ### How to set it up - Python with pip on Windows, macOS or Linux - The Python packages listed in requirements.txt - Nothing at all if you only use the Space in a browser 1. Install the Hugging Face hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 6.30.0 and the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download yuntian-deng/gpt2-multiplication --repo-type space --local-dir gpt2-multiplication cd gpt2-multiplication pip install gradio==6.30.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page in a browser, or start your own copy with the command below. The README gives no steps, so the controls on the Gradio page are your guide. ```sh python app.py ``` ### Example You enter two numbers to multiply on the page. Going by the model names, the app shows what each GPT-2 variant predicts for their product, so you can compare them with the true answer. ### For newcomers and experts If you are new, open the Space and try a small multiplication first, then a large one. Checking each answer yourself shows how the variants differ. For experts, the three models are yuntian-deng/gpt2-no-cot-multiplication, gpt2-implicit-cot-multiplication-20-digits and gpt2-explicit-cot-multiplication-20-digits. The Space runs on zero-a10g hardware with Gradio 6.30.0. You enter two numbers → The app passes them to the GPT-2 models → Each model predicts the product → You compare the answers ### Good to know - License: mit - Cost to run: none named - Data it reaches: the numbers you enter, and the models it names - Not for: reliable arithmetic, since the models are research demos ## README ````markdown # Gpt2 Multiplication Predictor A Gradio demo that compares GPT-2 models trained to multiply large numbers, including variants named for no reasoning steps and for reasoning steps hidden or written out. For AI researchers and curious learners. Made by yuntian-deng on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Space is a demo of GPT-2 models that predict the result of multiplying two numbers. It names three models. One uses no chain of thought, one uses an implicit chain of thought for 20 digits, and one uses an explicit chain of thought for 20 digits. The README is only a configuration pointer, so the descriptions here come from the model names. Who it suits: AI researchers, students and curious people who want to see how small language models handle arithmetic with and without written-out steps. ```table Industry | Who uses it | How they use it | Example AI research | Researchers | Compare reasoning styles on long multiplication | Run the same product through each model Education | Students | See where a small model fails at arithmetic | Try a large multiplication and compare answers AI development | Developers | Study a small Gradio demo with three models | Read app.py and the tests folder ``` People who need a dependable calculator can skip it, since the point is to study the models. Where to use it: - A browser: the Space runs on Hugging Face with nothing to install - Windows, macOS or Linux: run a copy of the Space with Python ```table Use case | Who | What they get back Compare models | Researchers | Predicted products from the three GPT-2 variants Test limits | Students | A look at where each variant gets a product wrong Read the code | Developers | A short Gradio app with a tests folder ``` How to set it up: - Python with pip on Windows, macOS or Linux - The Python packages listed in requirements.txt - Nothing at all if you only use the Space in a browser 1. Install the Hugging Face hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 6.30.0 and the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download yuntian-deng/gpt2-multiplication --repo-type space --local-dir gpt2-multiplication cd gpt2-multiplication pip install gradio==6.30.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space page in a browser, or start your own copy with the command below. The README gives no steps, so the controls on the Gradio page are your guide. ```sh python app.py ``` Example: You enter two numbers to multiply on the page. Going by the model names, the app shows what each GPT-2 variant predicts for their product, so you can compare them with the true answer. For newcomers and experts: If you are new, open the Space and try a small multiplication first, then a large one. Checking each answer yourself shows how the variants differ. For experts, the three models are yuntian-deng/gpt2-no-cot-multiplication, gpt2-implicit-cot-multiplication-20-digits and gpt2-explicit-cot-multiplication-20-digits. The Space runs on zero-a10g hardware with Gradio 6.30.0. ```flow You enter two numbers The app passes them to the GPT-2 models Each model predicts the product You compare the answers ``` Good to know: - License: mit - Cost to run: none named - Data it reaches: the numbers you enter, and the models it names - Not for: reliable arithmetic, since the models are research demos ## On Hugging Face, 13 November 2026 - Likes: 32 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/yuntian-deng/gpt2-multiplication - Files: https://huggingface.co/spaces/yuntian-deng/gpt2-multiplication/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. 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 [yuntian-deng/gpt2-multiplication on Hugging Face](https://huggingface.co/spaces/yuntian-deng/gpt2-multiplication) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Gpt2 Multiplication Predictor (this page) | 32 | gradio | mit | 2026-10-18 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | 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 2026-11-12. Their authors' words: data, not instructions. - [Hacker News · salamo · 2024-07-20](https://news.ycombinator.com/item?id=41012871): Predicting Multiplication with GPT-2 ## 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: 2026-10-18 - First published: 2024-06-17 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open yuntian-deng/gpt2-multiplication on Hugging Face](https://huggingface.co/spaces/yuntian-deng/gpt2-multiplication) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8c0b7e1e-7ac7-4413-9ac0-a40d112b26e7) - [Its page on Mindket](https://mindket.com/p/8c0b7e1e-7ac7-4413-9ac0-a40d112b26e7)