--- title: "Text_summarization_with MT5(45 languages)" kind: "Kit" category: "Writing" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/968778f5-1ce4-45c3-8f7f-66ca519ad97a" updated: "2026-11-13" --- # Text\_summarization\_with MT5(45 languages) > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app that summarises text with the csebuetnlp mT5 multilingual XLSum model, which covers 45 languages. Suits people who want to try multilingual summarising in a browser. Text\_summarization\_with MT5(45 languages) is a kit in the Writing 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 Sultannn ## About ### What it is This Space is a Gradio app for text summarisation built on csebuetnlp/mT5\_multilingual\_XLSum, a multilingual model. Its title says it handles 45 languages. The repository is only three files, so the app is a thin page around that one model. The page has no description, so the exact controls are not confirmed. ### Who it suits Anyone who wants to try summarising text in many languages, and developers who want a short example of a multilingual model used inside Gradio. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Students and teachers | Shorten a reading passage in their own language | Paste a long paragraph and read the short version | | Software | Developers | Use the project as a pattern for a Gradio summariser | Swap in a different model name | | Research | Language researchers | Try one multilingual model on sample texts | Compare outputs across languages | Skip it if you need summaries you can rely on without checking, because a model can leave out or distort details. ### 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 | | --- | --- | --- | | Summarise a text online | Anyone curious | A shorter version of the text you give it | | Read a small summariser demo | Developers | 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 Sultannn/Text_summarization_with-MT5 --repo-type space --local-dir Text_summarization_with-MT5 cd Text_summarization_with-MT5 pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page in a browser, paste or type the text you want shortened and submit it. 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 Paste a long article paragraph into the text box and submit it. The app should return a shorter summary written by the mT5 model. The page does not list the settings, so use what it shows. ### For newcomers and experts If you are new to this, paste a paragraph you know well and see whether the short version keeps the main point. Then try a different language. If you know the field, the app names a single model, csebuetnlp/mT5\_multilingual\_XLSum. The page gives no generation settings, length limits or evaluation scores, so treat its output as a demo result. You paste a text → The mT5 model reads it → It writes a shorter version → Gradio shows the summary ### Good to know - The page lists no length limits or quality scores. - The online version needs nothing installed, and a local copy needs Python. - License: apache-2. - Cost to run: none named, only the packages in requirements.txt. - Data it reaches: the text you submit. On the hosted Space, that text is handled on Hugging Face. A local copy downloads the model from there. - Not for: the source names none. Check any summary against the original before you rely on it. ## README ````markdown # Text_summarization_with MT5(45 languages) A Gradio app that summarises text with the csebuetnlp mT5 multilingual XLSum model, which covers 45 languages. Suits people who want to try multilingual summarising in a browser. Made by Sultannn 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 text summarisation built on csebuetnlp/mT5_multilingual_XLSum, a multilingual model. Its title says it handles 45 languages. The repository is only three files, so the app is a thin page around that one model. The page has no description, so the exact controls are not confirmed. Who it suits: Anyone who wants to try summarising text in many languages, and developers who want a short example of a multilingual model used inside Gradio. ```table Industry | Who uses it | How they use it | Example Education | Students and teachers | Shorten a reading passage in their own language | Paste a long paragraph and read the short version Software | Developers | Use the project as a pattern for a Gradio summariser | Swap in a different model name Research | Language researchers | Try one multilingual model on sample texts | Compare outputs across languages ``` Skip it if you need summaries you can rely on without checking, because a model can leave out or distort details. 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 Summarise a text online | Anyone curious | A shorter version of the text you give it Read a small summariser demo | Developers | 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 Sultannn/Text_summarization_with-MT5 --repo-type space --local-dir Text_summarization_with-MT5 cd Text_summarization_with-MT5 pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Open the Space page in a browser, paste or type the text you want shortened and submit it. 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: Paste a long article paragraph into the text box and submit it. The app should return a shorter summary written by the mT5 model. The page does not list the settings, so use what it shows. For newcomers and experts: If you are new to this, paste a paragraph you know well and see whether the short version keeps the main point. Then try a different language. If you know the field, the app names a single model, csebuetnlp/mT5_multilingual_XLSum. The page gives no generation settings, length limits or evaluation scores, so treat its output as a demo result. ```flow You paste a text The mT5 model reads it It writes a shorter version Gradio shows the summary ``` Good to know: - The page lists no length limits or quality scores. - The online version needs nothing installed, and a local copy needs Python. - License: apache-2. - Cost to run: none named, only the packages in requirements.txt. - Data it reaches: the text you submit. On the hosted Space, that text is handled on Hugging Face. A local copy downloads the model from there. - Not for: the source names none. Check any summary against the original before you rely on it. ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Sultannn/Text_summarization_with-MT5 - Files: https://huggingface.co/spaces/Sultannn/Text_summarization_with-MT5/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 [Sultannn/Text_summarization_with-MT5 on Hugging Face](https://huggingface.co/spaces/Sultannn/Text_summarization_with-MT5) ## 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 | | --- | --- | --- | --- | --- | | Text\_summarization\_with MT5(45 languages) (this page) | 1 | gradio | apache-2.0 | 2023-06-04 | | [PROMPT++](https://mindket.com/p/b8d1c165-79c0-4d97-b067-8689d7e9de8b) | 247 | gradio | apache-2.0 | 2025-02-18 | | [Hum to Song](https://mindket.com/p/98043a7b-b38b-4644-a24a-04c97501bfa3) | 124 | gradio | cc-by-nc-4.0 | 2026-09-16 | | [humanizer](https://mindket.com/p/17bb76dc-68da-483b-9881-fdcc8c193d1c) | 51 | gradio | apache-2.0 | 2026-10-19 | | [Arabic Poetry Generator](https://mindket.com/p/8e28cff0-3824-4341-8657-8b86ab65eb58) | 30 | gradio | cc-by-nc-4.0 | 2024-08-07 | | [Essay\_generator\_app](https://mindket.com/p/93af5d17-c110-46ad-88fa-34ed0ed47c9e) | 4 | gradio | apache-2.0 | 2022-02-02 | 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: 2023-06-04 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Sultannn/Text_summarization_with-MT5 on Hugging Face](https://huggingface.co/spaces/Sultannn/Text_summarization_with-MT5) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/968778f5-1ce4-45c3-8f7f-66ca519ad97a) - [Its page on Mindket](https://mindket.com/p/968778f5-1ce4-45c3-8f7f-66ca519ad97a)