--- title: "Projected_gan" kind: "Kit" category: "Education" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8f43707b-8637-449b-9276-409e8e9c91eb" updated: "2026-11-13" --- # Projected\_gan > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo built on a Projected GAN model trained on Pokemon pictures, published as an example by the Stanford-CS236g account. Suits students who want to see a generative image model run in a browser. Projected\_gan is a kit in the Education 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 Stanford-CS236g ## About ### What it is Projected\_gan is a small Gradio app that wraps the Projected\_GAN\_Pokemon model from autonomousvision. The Space sits under the Stanford-CS236g account and the word example appears in its address, so it reads as a teaching sample. It looks like a GAN that makes Pokemon style pictures. The page has no description, so the details are not confirmed. ### Who it suits Students and developers who want to see a generative adversarial network produce images, or who want a short example of a model wrapped in a Gradio page. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Students of generative models | Run the demo and read app.py to see how the model is loaded | Generate a picture and study the result | | Software | Developers | Use the project as a pattern for a Gradio image generator | Point it at a different model name | | Research | Hobbyists | Look at what a Projected GAN produces on one subject | Compare several generated pictures | Skip it if you need an image generator you can steer with text, because the page does not describe any such control. ### Where to use it - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Try a GAN online | Anyone curious | A generated Pokemon style picture | | Read a small model demo | Students | A three file Python project to study | ### How to set it up - Nothing to install for the online version - Python on your computer for a local copy - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space's files to a folder. 3. Move into that folder. 4. Install gradio, then the packages from requirements.txt. 5. Start the app with app.py. ```sh pip install -U huggingface_hub hf download Stanford-CS236g/example-pokemon-gan --repo-type space --local-dir example-pokemon-gan cd example-pokemon-gan pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page in a browser and use the controls it shows. For a local copy, run the app and open the page Gradio opens for you. ```sh python app.py ``` | Tool | What it does | | --- | --- | | python app.py | Starts the Gradio app on your computer | | hf download | Copies the Space's files into a local folder | ### Example Open the Space and start a run with its button. The app should show a picture made by the Pokemon model. The page does not list the controls, so follow what the page offers. ### For newcomers and experts If you are new to this, open the Space and generate a few pictures to get a feel for what a GAN makes. The repository has only app.py and requirements.txt besides the readme, so it is easy to read in one sitting. If you know the field, the app names one model, autonomousvision/Projected\_GAN\_Pokemon. The Space itself holds no weights, so the model files come from that model repository. Sampling settings and image size are not stated. The app loads the named model → You start a run → The GAN makes a picture → Gradio shows it ### Good to know - The page gives no description, sample count or quality figures. - The online version needs nothing installed, and a local copy needs Python. - License: mit. - Cost to run: none named, only the packages in requirements.txt. - Data it reaches: it downloads the named model from Hugging Face. The source names no account or other service. - Not for: the source names none. ## README ````markdown # Projected_gan A Gradio demo built on a Projected GAN model trained on Pokemon pictures, published as an example by the Stanford-CS236g account. Suits students who want to see a generative image model run in a browser. Made by Stanford-CS236g 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: Projected_gan is a small Gradio app that wraps the Projected_GAN_Pokemon model from autonomousvision. The Space sits under the Stanford-CS236g account and the word example appears in its address, so it reads as a teaching sample. It looks like a GAN that makes Pokemon style pictures. The page has no description, so the details are not confirmed. Who it suits: Students and developers who want to see a generative adversarial network produce images, or who want a short example of a model wrapped in a Gradio page. ```table Industry | Who uses it | How they use it | Example Education | Students of generative models | Run the demo and read app.py to see how the model is loaded | Generate a picture and study the result Software | Developers | Use the project as a pattern for a Gradio image generator | Point it at a different model name Research | Hobbyists | Look at what a Projected GAN produces on one subject | Compare several generated pictures ``` Skip it if you need an image generator you can steer with text, because the page does not describe any such control. Where to use it: - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy ```table Use case | Who | What they get back Try a GAN online | Anyone curious | A generated Pokemon style picture Read a small model demo | Students | A three file Python project to study ``` How to set it up: - Nothing to install for the online version - Python on your computer for a local copy - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space's files to a folder. 3. Move into that folder. 4. Install gradio, then the packages from requirements.txt. 5. Start the app with app.py. ```sh pip install -U huggingface_hub hf download Stanford-CS236g/example-pokemon-gan --repo-type space --local-dir example-pokemon-gan cd example-pokemon-gan pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Open the Space page in a browser and use the controls it shows. For a local copy, run the app and open the page Gradio opens for you. ```sh python app.py ``` ```table Tool | What it does python app.py | Starts the Gradio app on your computer hf download | Copies the Space's files into a local folder ``` Example: Open the Space and start a run with its button. The app should show a picture made by the Pokemon model. The page does not list the controls, so follow what the page offers. For newcomers and experts: If you are new to this, open the Space and generate a few pictures to get a feel for what a GAN makes. The repository has only app.py and requirements.txt besides the readme, so it is easy to read in one sitting. If you know the field, the app names one model, autonomousvision/Projected_GAN_Pokemon. The Space itself holds no weights, so the model files come from that model repository. Sampling settings and image size are not stated. ```flow The app loads the named model You start a run The GAN makes a picture Gradio shows it ``` Good to know: - The page gives no description, sample count or quality figures. - The online version needs nothing installed, and a local copy needs Python. - License: mit. - Cost to run: none named, only the packages in requirements.txt. - Data it reaches: it downloads the named model from Hugging Face. The source names no account or other service. - Not for: the source names none. ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/Stanford-CS236g/example-pokemon-gan - Files: https://huggingface.co/spaces/Stanford-CS236g/example-pokemon-gan/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 [Stanford-CS236g/example-pokemon-gan on Hugging Face](https://huggingface.co/spaces/Stanford-CS236g/example-pokemon-gan) ## 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 | | --- | --- | --- | --- | --- | | Projected\_gan (this page) | 1 | gradio | mit | 2022-02-18 | | [Unit 1 Quiz - AI Agent Fundementals](https://mindket.com/p/1b65056a-a2b2-4179-a81c-bdffa3636205) | 360 | gradio | apache-2.0 | 2025-06-24 | | [Unit 2.1 smolagents Code Quiz](https://mindket.com/p/c9f42604-0003-4117-9a4b-2b785f68ee99) | 63 | gradio | apache-2.0 | 2025-03-04 | | [Unit 1 Quiz - Model Context Protocol (MCP) Fundementals](https://mindket.com/p/f7210665-ca4c-423f-b45d-a1c6fa549eec) | 58 | gradio | apache-2.0 | 2025-06-03 | | [Tamazight Text-to-Speech](https://mindket.com/p/ab94f6a3-34fa-4c03-9fd0-751ff4f282eb) | 41 | gradio | cc-by-4.0 | 2023-11-25 | | [Embedding Draw Challenge](https://mindket.com/p/76690a14-5bc9-4d53-ad3e-d47e7218918f) | 30 | gradio | apache-2.0 | 2026-10-06 | 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: 2022-02-18 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Stanford-CS236g/example-pokemon-gan on Hugging Face](https://huggingface.co/spaces/Stanford-CS236g/example-pokemon-gan) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8f43707b-8637-449b-9276-409e8e9c91eb) - [Its page on Mindket](https://mindket.com/p/8f43707b-8637-449b-9276-409e8e9c91eb)