--- title: "Practica1" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/d7390aba-b048-4cdf-a274-656113451975" updated: "2026-11-12" --- # Practica1 > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app that runs a saved model on pictures, with two sample pictures of buildings and a forest. It suits people who want to try a small image model in a browser. Practica1 is a kit in the Developer 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 AP2122 ## About ### What it is Practica1 is a Gradio app on Hugging Face Spaces that runs a saved model on pictures. The repository holds app.py, an exported model file named export.pkl and two sample pictures, one of buildings and one of a forest. The README gives no description, so the exact classes are clear only on the page. ### Who it suits It suits people who want to try a small image model in a browser, and students who want to see how an exported model file is used in a Gradio page. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Students | Read app.py to see how the saved model is loaded | Download the Space and open app.py | | Machine learning | Hobbyists | Try the model on the two sample pictures | Click the forest picture on the Space page | | Teaching | Instructors | Show a finished course exercise as a web page | Run the Space in a lesson | Anyone who needs documented classes, accuracy or training steps can skip it, since the source gives none. ### Where to use it - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy | Use case | Who | What they get back | | --- | --- | --- | | Try the model online | Anyone curious | A prediction for the picture, shown in the browser | | Study an exported model demo | Learners | An app file, a model file and two sample pictures | ### How to set it up Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface\_hub package, to fetch the files - The packages in requirements.txt, plus Gradio 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called Practica1. 3. Move into that folder. 4. Install Gradio, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download AP2122/Practica1 --repo-type space --local-dir Practica1 cd Practica1 pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page on Hugging Face, then give it a picture or pick a sample. For a local copy, run python app.py in the folder and open the page it starts. ### Example You pick the buildings picture on the Space page. The app runs its saved model on it and shows the prediction for the picture. ### For newcomers and experts If you are new, click one of the two sample pictures first. That shows the whole idea in one step, with nothing to install. If you know the field, the weights live in export.pkl inside the repository, so the app needs no outside model download that the source names. The training data, the class list and the accuracy are not described. You open the page and choose a picture → app.py loads the saved model file → The prediction shows in your browser ### Good to know - The README gives no description, so the exact classes are clear only on the page - It needs Gradio and the packages in requirements.txt - License: cc0-1 - Cost to run: none named - Data it reaches: the pictures you give it and the model file in its own repository ## README ````markdown # Practica1 A Gradio app that runs a saved model on pictures, with two sample pictures of buildings and a forest. It suits people who want to try a small image model in a browser. Made by AP2122 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: Practica1 is a Gradio app on Hugging Face Spaces that runs a saved model on pictures. The repository holds app.py, an exported model file named export.pkl and two sample pictures, one of buildings and one of a forest. The README gives no description, so the exact classes are clear only on the page. Who it suits: It suits people who want to try a small image model in a browser, and students who want to see how an exported model file is used in a Gradio page. ```table Industry | Who uses it | How they use it | Example Education | Students | Read app.py to see how the saved model is loaded | Download the Space and open app.py Machine learning | Hobbyists | Try the model on the two sample pictures | Click the forest picture on the Space page Teaching | Instructors | Show a finished course exercise as a web page | Run the Space in a lesson ``` Anyone who needs documented classes, accuracy or training steps can skip it, since the source gives none. Where to use it: - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy ```table Use case | Who | What they get back Try the model online | Anyone curious | A prediction for the picture, shown in the browser Study an exported model demo | Learners | An app file, a model file and two sample pictures ``` How to set it up: Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface_hub package, to fetch the files - The packages in requirements.txt, plus Gradio 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called Practica1. 3. Move into that folder. 4. Install Gradio, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download AP2122/Practica1 --repo-type space --local-dir Practica1 cd Practica1 pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Open the Space page on Hugging Face, then give it a picture or pick a sample. For a local copy, run python app.py in the folder and open the page it starts. Example: You pick the buildings picture on the Space page. The app runs its saved model on it and shows the prediction for the picture. For newcomers and experts: If you are new, click one of the two sample pictures first. That shows the whole idea in one step, with nothing to install. If you know the field, the weights live in export.pkl inside the repository, so the app needs no outside model download that the source names. The training data, the class list and the accuracy are not described. ```flow You open the page and choose a picture app.py loads the saved model file The prediction shows in your browser ``` Good to know: - The README gives no description, so the exact classes are clear only on the page - It needs Gradio and the packages in requirements.txt - License: cc0-1 - Cost to run: none named - Data it reaches: the pictures you give it and the model file in its own repository ## On Hugging Face, 13 November 2026 - Likes: 10 - Built with: gradio - License: cc0-1.0 ## Links - Space: https://huggingface.co/spaces/AP2122/Practica1 - Files: https://huggingface.co/spaces/AP2122/Practica1/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 [AP2122/Practica1 on Hugging Face](https://huggingface.co/spaces/AP2122/Practica1) ## 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 | | --- | --- | --- | --- | --- | | Practica1 (this page) | 10 | gradio | cc0-1.0 | 2022-03-08 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | | [Z Image Turbo](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a) | 1,940 | gradio | apache-2.0 | 2026-05-22 | Numbers as Mindket last read them, on 2026-11-12. ## 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: 2022-03-08 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open AP2122/Practica1 on Hugging Face](https://huggingface.co/spaces/AP2122/Practica1) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/d7390aba-b048-4cdf-a274-656113451975) - [Its page on Mindket](https://mindket.com/p/d7390aba-b048-4cdf-a274-656113451975)