--- title: "KITScenes LongTail Challenges" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/81d4b5b7-b26b-4f1e-80d6-c5e1f14b3030" updated: "2026-11-12" --- # KITScenes LongTail Challenges > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app for the KITScenes LongTail challenges, tied to a dataset of the same name and two named models. The README is nearly empty, so its tasks and scoring are not described. KITScenes LongTail Challenges is a kit in the Research 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 KIT-MRT ## About ### What it is This Space is a Gradio app for the KITScenes LongTail challenges. It names a dataset called KITScenes-LongTail and two models, google/embeddinggemma-300m and q-future/one-align. The README holds little more than the title, so the tasks, rules and scoring are not described. ### Who it suits It suits researchers and students who follow the KITScenes LongTail dataset, and developers who want to read how a challenge page is built in Gradio. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Dataset users | Open the page to see what the challenge is about | Viewing the hosted app before using the dataset | | Machine learning | Developers | Read how the app uses its two named models | Reading app.py and the src folder | | Education | Students | Study a small Gradio project with a license file | Running a local copy and looking at the files | Skip it if you need documented challenge rules, because the source does not include them. ### Where to use it You can open it online or run a copy on your own computer. - A web browser, on the Space's page at Hugging Face - Python on a Windows, macOS or Linux computer | Use case | Who | What they get back | | --- | --- | --- | | Try the hosted app | Anyone | The running app in a browser tab | | Run a local copy | Developers | The same app on their own computer | | Read the code | Students | A Gradio project with app.py, a src folder and a media folder | ### How to set it up Online use needs nothing, and it runs on basic CPU hardware at Hugging Face. A local copy needs Python and pip. - Python and pip - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space into a folder and move into it. 3. Install Gradio 6.31.0 and then the listed packages. 4. Start app.py. ```sh pip install -U huggingface_hub hf download KIT-MRT/KITScenes-LongTail-Challenge --repo-type space --local-dir KITScenes-LongTail-Challenge cd KITScenes-LongTail-Challenge pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` ### How to use it Start the app with one command and watch the terminal, where Gradio apps usually print the address of the running page. Open that address in your browser and use the controls it shows. ```sh python app.py ``` ### Example You could run the steps above and open the page to see what the challenge offers. The README gives no sample entry or result, so what comes back is not documented. ### For newcomers and experts If you are new, open the hosted Space first and read what the page shows. Download the files only when you want to see how it works. If you know the field, the app names an embedding model and the one-align model, plus the KITScenes-LongTail dataset. The README does not say how they are combined, whether scoring runs on the Space or what a submission looks like. Download the Space → Install requirements → Run app.py → Open the Gradio page ### Good to know The README is nearly empty, so the challenge itself is not explained. - License: mit - Cost to run: none named - Data it reaches: it names the KITScenes-LongTail dataset and two models, and the source mentions no account - Not for: the source states no limits, and it does not describe what the challenge asks of entrants ## README ````markdown # KITScenes LongTail Challenges A Gradio app for the KITScenes LongTail challenges, tied to a dataset of the same name and two named models. The README is nearly empty, so its tasks and scoring are not described. Made by KIT-MRT 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 app for the KITScenes LongTail challenges. It names a dataset called KITScenes-LongTail and two models, google/embeddinggemma-300m and q-future/one-align. The README holds little more than the title, so the tasks, rules and scoring are not described. Who it suits: It suits researchers and students who follow the KITScenes LongTail dataset, and developers who want to read how a challenge page is built in Gradio. ```table Industry | Who uses it | How they use it | Example Research | Dataset users | Open the page to see what the challenge is about | Viewing the hosted app before using the dataset Machine learning | Developers | Read how the app uses its two named models | Reading app.py and the src folder Education | Students | Study a small Gradio project with a license file | Running a local copy and looking at the files ``` Skip it if you need documented challenge rules, because the source does not include them. Where to use it: You can open it online or run a copy on your own computer. - A web browser, on the Space's page at Hugging Face - Python on a Windows, macOS or Linux computer ```table Use case | Who | What they get back Try the hosted app | Anyone | The running app in a browser tab Run a local copy | Developers | The same app on their own computer Read the code | Students | A Gradio project with app.py, a src folder and a media folder ``` How to set it up: Online use needs nothing, and it runs on basic CPU hardware at Hugging Face. A local copy needs Python and pip. - Python and pip - The packages listed in requirements.txt 1. Install the Hugging Face hub package. 2. Download the Space into a folder and move into it. 3. Install Gradio 6.31.0 and then the listed packages. 4. Start app.py. ```sh pip install -U huggingface_hub hf download KIT-MRT/KITScenes-LongTail-Challenge --repo-type space --local-dir KITScenes-LongTail-Challenge cd KITScenes-LongTail-Challenge pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` How to use it: Start the app with one command and watch the terminal, where Gradio apps usually print the address of the running page. Open that address in your browser and use the controls it shows. ```sh python app.py ``` Example: You could run the steps above and open the page to see what the challenge offers. The README gives no sample entry or result, so what comes back is not documented. For newcomers and experts: If you are new, open the hosted Space first and read what the page shows. Download the files only when you want to see how it works. If you know the field, the app names an embedding model and the one-align model, plus the KITScenes-LongTail dataset. The README does not say how they are combined, whether scoring runs on the Space or what a submission looks like. ```flow Download the Space Install requirements Run app.py Open the Gradio page ``` Good to know: The README is nearly empty, so the challenge itself is not explained. - License: mit - Cost to run: none named - Data it reaches: it names the KITScenes-LongTail dataset and two models, and the source mentions no account - Not for: the source states no limits, and it does not describe what the challenge asks of entrants ## On Hugging Face, 13 November 2026 - Likes: 15 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/KIT-MRT/KITScenes-LongTail-Challenge - Files: https://huggingface.co/spaces/KIT-MRT/KITScenes-LongTail-Challenge/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 [KIT-MRT/KITScenes-LongTail-Challenge on Hugging Face](https://huggingface.co/spaces/KIT-MRT/KITScenes-LongTail-Challenge) ## 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 | | --- | --- | --- | --- | --- | | KITScenes LongTail Challenges (this page) | 15 | gradio | mit | 2026-11-08 | | [MTEB-BR Leaderboard](https://mindket.com/p/05f89589-d44c-4616-8efb-c50c9ba6ad94) | 126 | static | apache-2.0 | 2026-07-29 | | [Outsmart](https://mindket.com/p/bc535e3d-8da3-4481-bb74-8405891098d4) | 62 | streamlit | mit | 2026-10-21 | | [DialFork Leaderboard](https://mindket.com/p/ce936e47-6d26-4d6f-a1b7-9c21abf49629) | 2 | static | mit | 2026-11-05 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Open VLM Video Leaderboard](https://mindket.com/p/6cbb4dc8-fd02-4668-a8d1-8e915f3c3d1f) | 136 | gradio | apache-2.0 | 2024-11-21 | 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: 2026-11-08 - First published: 2026-03-31 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open KIT-MRT/KITScenes-LongTail-Challenge on Hugging Face](https://huggingface.co/spaces/KIT-MRT/KITScenes-LongTail-Challenge) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/81d4b5b7-b26b-4f1e-80d6-c5e1f14b3030) - [Its page on Mindket](https://mindket.com/p/81d4b5b7-b26b-4f1e-80d6-c5e1f14b3030)