--- title: "Demo Integrated Gradients Alibi Gradio" kind: "Kit" category: "Education" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/3c458aaf-82db-4b0c-8c1c-28b21d4815cf" updated: "2026-11-13" --- # Demo Integrated Gradients Alibi Gradio > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo that, going by its title, shows the integrated gradients explanation method from the Alibi library. Suits students and developers who want to see how a model's prediction can be explained. Demo Integrated Gradients Alibi Gradio 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 mawady ## About ### What it is This Space is a Gradio demo by mawady. Its title names integrated gradients and Alibi, so it appears to show that explanation method on a model's prediction. Integrated gradients is usually used to show which parts of an input pushed a model toward its answer. The page has no description, so the model and inputs are not confirmed. ### Who it suits Students and developers who want to see model explanation in practice, and anyone who wants a short Gradio example of an explainability tool. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Machine learning students | Run the demo to see what an attribution method shows | Open the Space and look at the highlighted result | | Software | Developers | Use the project as a pattern for an explainability demo in Gradio | Swap in their own model | | Research | Interpretability readers | Look at one attribution method on a sample | Compare the explanation with their expectation | Skip it if you need a full explainability toolkit, because this is a three file demo. ### Where to use it - A web browser, on the Space's page on Hugging Face - Python on Windows, macOS or Linux, using a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Try an explanation method online | Anyone curious | The explanation the demo produces for its sample | | Study a short explainability demo | Developers | A small Python project built around Alibi | ### 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 mawady/Demo-integrated-gradients-alibi-gradio --repo-type space --local-dir Demo-integrated-gradients-alibi-gradio cd Demo-integrated-gradients-alibi-gradio 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 run its default input. The page should show the explanation the method produces for that input. The page does not describe the controls or the output, so follow what you see. ### For newcomers and experts If you are new to this, open the Space and run it once with the default input. Then read the result as a hint about what the model paid attention to, not as proof. If you know the field, the title points to Alibi's integrated gradients. The page does not name the model, the baseline or the number of steps, so read app.py before you draw conclusions from it. An input goes in → A model makes a prediction → Integrated gradients scores the input → Gradio shows the explanation ### Good to know - The page gives no description of the model, input or output. - 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: only the input you give it. The source names no account or other service. - Not for: the source names none. ## README ````markdown # Demo Integrated Gradients Alibi Gradio A Gradio demo that, going by its title, shows the integrated gradients explanation method from the Alibi library. Suits students and developers who want to see how a model's prediction can be explained. Made by mawady 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 Gradio demo by mawady. Its title names integrated gradients and Alibi, so it appears to show that explanation method on a model's prediction. Integrated gradients is usually used to show which parts of an input pushed a model toward its answer. The page has no description, so the model and inputs are not confirmed. Who it suits: Students and developers who want to see model explanation in practice, and anyone who wants a short Gradio example of an explainability tool. ```table Industry | Who uses it | How they use it | Example Education | Machine learning students | Run the demo to see what an attribution method shows | Open the Space and look at the highlighted result Software | Developers | Use the project as a pattern for an explainability demo in Gradio | Swap in their own model Research | Interpretability readers | Look at one attribution method on a sample | Compare the explanation with their expectation ``` Skip it if you need a full explainability toolkit, because this is a three file demo. Where to use it: - A web browser, on the Space's page on Hugging Face - Python on Windows, macOS or Linux, using a downloaded copy ```table Use case | Who | What they get back Try an explanation method online | Anyone curious | The explanation the demo produces for its sample Study a short explainability demo | Developers | A small Python project built around Alibi ``` 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 mawady/Demo-integrated-gradients-alibi-gradio --repo-type space --local-dir Demo-integrated-gradients-alibi-gradio cd Demo-integrated-gradients-alibi-gradio 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 run its default input. The page should show the explanation the method produces for that input. The page does not describe the controls or the output, so follow what you see. For newcomers and experts: If you are new to this, open the Space and run it once with the default input. Then read the result as a hint about what the model paid attention to, not as proof. If you know the field, the title points to Alibi's integrated gradients. The page does not name the model, the baseline or the number of steps, so read app.py before you draw conclusions from it. ```flow An input goes in A model makes a prediction Integrated gradients scores the input Gradio shows the explanation ``` Good to know: - The page gives no description of the model, input or output. - 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: only the input you give it. The source names no account or other service. - Not for: the source names none. ## On Hugging Face, 13 November 2026 - Likes: 2 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/mawady/Demo-integrated-gradients-alibi-gradio - Files: https://huggingface.co/spaces/mawady/Demo-integrated-gradients-alibi-gradio/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 [mawady/Demo-integrated-gradients-alibi-gradio on Hugging Face](https://huggingface.co/spaces/mawady/Demo-integrated-gradients-alibi-gradio) ## 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 | | --- | --- | --- | --- | --- | | Demo Integrated Gradients Alibi Gradio (this page) | 2 | gradio | mit | 2023-04-19 | | [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: 2023-04-19 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open mawady/Demo-integrated-gradients-alibi-gradio on Hugging Face](https://huggingface.co/spaces/mawady/Demo-integrated-gradients-alibi-gradio) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3c458aaf-82db-4b0c-8c1c-28b21d4815cf) - [Its page on Mindket](https://mindket.com/p/3c458aaf-82db-4b0c-8c1c-28b21d4815cf)