Clasificador_de_mascotas

Clasificador_de_mascotas

A Gradio app, the name meaning pet classifier in Spanish, that runs a saved model on pet photos, with three sample photos. It suits people who want to try a small image model.

Made by cabustillo13 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: Clasificador_de_mascotas is a Gradio app on Hugging Face Spaces. The name is Spanish for pet classifier, and the repository holds a saved model file named export.pkl with three sample photos: an Egyptian cat, a Siberian husky and a pit bull. The README gives no description beyond its settings.

Who it suits: It suits people who want to try a small pet photo classifier in a browser, and Spanish-speaking learners who want to see how an exported model 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
Pet care | Pet owners | Try the classifier on a photo of their pet | Open the Space and give it a picture
Teaching | Instructors | Show a finished course project as a web page | Click a sample photo in class

Anyone who needs a documented list of breeds or measured accuracy can skip it, since the README 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
Classify a pet photo | Pet owners | A prediction for the picture, shown in the browser
Study an exported model demo | Learners | An app file, a model file and three sample photos

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 clasificador_de_mascotas.
3. Move into that folder.
4. Install Gradio, then the packages from requirements.txt.
5. Start the app.

pip install -U huggingface_hub
hf download cabustillo13/clasificador_de_mascotas --repo-type space --local-dir clasificador_de_mascotas
cd clasificador_de_mascotas
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 photo. For a local copy, run python app.py in the folder and open the page it starts.

Example: You pick the Siberian husky photo 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 three sample photos 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 photo
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: mit
• 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: 0
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/cabustillo13/clasificador_de_mascotas
• Files: https://huggingface.co/spaces/cabustillo13/clasificador_de_mascotas/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.