Mindket

Gpt2 Multiplication Predictor

Newversion 1 · updated

Overview

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 . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • 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
Runs in
  • A browser: the Space runs on Hugging Face with nothing to install
  • Windows, macOS or Linux: run a copy of the Space with Python
Start with
pip install -U huggingface_hub
hf download yuntian-deng/gpt2-multiplication --repo-type space --local-dir gpt2-multiplication
cd gpt2-multiplication

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

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.

IndustryWho uses itHow they use itExample
AI researchResearchersCompare reasoning styles on long multiplicationRun the same product through each model
EducationStudentsSee where a small model fails at arithmeticTry a large multiplication and compare answers
AI developmentDevelopersStudy a small Gradio demo with three modelsRead 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 caseWhoWhat they get back
Compare modelsResearchersPredicted products from the three GPT-2 variants
Test limitsStudentsA look at where each variant gets a product wrong
Read the codeDevelopersA 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.
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.

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.

  1. You enter two numbers
  2. The app passes them to the GPT-2 models
  3. Each model predicts the product
  4. 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 and files

README

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.

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.
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.

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

On Hugging Face, 13 November 2026

  • Likes: 32
  • Built with: gradio
  • License: mit

Links

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.

Files
README.md  4 KB

1 file, 4 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
Gpt2 Multiplication Predictor This page32gradiomit
Open VLM LeaderboardShares gradio1,034gradioapache-2.0
Face SwapShares gradio808gradiocc-by-nc-sa-4.0
TTS Spaces ArenaShares gradio493gradiozlib
Depth Anything 3Shares gradio490gradiocc-by-nc-4.0
BLIPShares gradio431gradiobsd-3-clause
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

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What people say

Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.

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