--- title: "Duygu_Analizi" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/89cec755-9754-4d5b-9952-e5738bb14a60" updated: "2026-11-12" --- # Duygu\_Analizi > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app for sentiment analysis of Turkish text using the savasy/bert-base-turkish-sentiment-cased model. It suits people who want to check the tone of Turkish sentences in a browser. Duygu\_Analizi 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 alperbayram ## About ### What it is Duygu\_Analizi is a Gradio app on Hugging Face Spaces for sentiment analysis of Turkish text. Duygu Analizi is Turkish for sentiment analysis. It names the savasy/bert-base-turkish-sentiment-cased model, and the code is app.py with a requirements.txt. ### Who it suits It suits people who want to check the sentiment of Turkish sentences in a browser, and learners who want a short example of a sentiment model behind a Gradio page. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Customer support | Analysts | Check whether a Turkish comment reads as positive or negative | Open the Space and enter a comment | | Marketing | Social media teams | Try sentiment on short Turkish posts | Paste a post into the text box | | Education | Students | Read app.py to see how a sentiment model is called | Download the Space and open app.py | Anyone who needs other languages or measured accuracy can skip it, since the source gives neither. ### 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 | | --- | --- | --- | | Score a Turkish sentence | Analysts | A sentiment result shown in the browser | | Study a sentiment demo | Learners | A short app file that calls one named model | ### 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 Duygu\_Analizi. 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 alperbayram/Duygu_Analizi --repo-type space --local-dir Duygu_Analizi cd Duygu_Analizi pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page on Hugging Face, enter a Turkish sentence and read the result. For a local copy, run python app.py in the folder and open the page it starts. ### Example You type a Turkish sentence that praises a product. The app sends it to the Turkish sentiment model and shows the sentiment it assigns to the sentence. ### For newcomers and experts If you are new, open the Space page and try one short Turkish sentence. Sentiment analysis means a program judges whether a text sounds positive or negative. If you know the field, this is a thin Gradio wrapper around one cased Turkish BERT sentiment model. The source gives no label set or accuracy, so check the model page for those. You type a Turkish sentence in the browser → app.py passes it to the sentiment model → The sentiment result shows on the page ### Good to know - It relies on one named model and covers Turkish text - It needs Gradio and the packages in requirements.txt - License: afl-3 - Cost to run: none named - Data it reaches: the savasy/bert-base-turkish-sentiment-cased model it names ## README ````markdown # Duygu_Analizi A Gradio app for sentiment analysis of Turkish text using the savasy/bert-base-turkish-sentiment-cased model. It suits people who want to check the tone of Turkish sentences in a browser. Made by alperbayram 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: Duygu_Analizi is a Gradio app on Hugging Face Spaces for sentiment analysis of Turkish text. Duygu Analizi is Turkish for sentiment analysis. It names the savasy/bert-base-turkish-sentiment-cased model, and the code is app.py with a requirements.txt. Who it suits: It suits people who want to check the sentiment of Turkish sentences in a browser, and learners who want a short example of a sentiment model behind a Gradio page. ```table Industry | Who uses it | How they use it | Example Customer support | Analysts | Check whether a Turkish comment reads as positive or negative | Open the Space and enter a comment Marketing | Social media teams | Try sentiment on short Turkish posts | Paste a post into the text box Education | Students | Read app.py to see how a sentiment model is called | Download the Space and open app.py ``` Anyone who needs other languages or measured accuracy can skip it, since the source gives neither. 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 Score a Turkish sentence | Analysts | A sentiment result shown in the browser Study a sentiment demo | Learners | A short app file that calls one named model ``` 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 Duygu_Analizi. 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 alperbayram/Duygu_Analizi --repo-type space --local-dir Duygu_Analizi cd Duygu_Analizi pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Open the Space page on Hugging Face, enter a Turkish sentence and read the result. For a local copy, run python app.py in the folder and open the page it starts. Example: You type a Turkish sentence that praises a product. The app sends it to the Turkish sentiment model and shows the sentiment it assigns to the sentence. For newcomers and experts: If you are new, open the Space page and try one short Turkish sentence. Sentiment analysis means a program judges whether a text sounds positive or negative. If you know the field, this is a thin Gradio wrapper around one cased Turkish BERT sentiment model. The source gives no label set or accuracy, so check the model page for those. ```flow You type a Turkish sentence in the browser app.py passes it to the sentiment model The sentiment result shows on the page ``` Good to know: - It relies on one named model and covers Turkish text - It needs Gradio and the packages in requirements.txt - License: afl-3 - Cost to run: none named - Data it reaches: the savasy/bert-base-turkish-sentiment-cased model it names ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: afl-3.0 ## Links - Space: https://huggingface.co/spaces/alperbayram/Duygu_Analizi - Files: https://huggingface.co/spaces/alperbayram/Duygu_Analizi/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 [alperbayram/Duygu_Analizi on Hugging Face](https://huggingface.co/spaces/alperbayram/Duygu_Analizi) ## 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 | | --- | --- | --- | --- | --- | | Duygu\_Analizi (this page) | 1 | gradio | afl-3.0 | 2022-02-27 | | [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: 2022-02-27 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open alperbayram/Duygu_Analizi on Hugging Face](https://huggingface.co/spaces/alperbayram/Duygu_Analizi) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/89cec755-9754-4d5b-9952-e5738bb14a60) - [Its page on Mindket](https://mindket.com/p/89cec755-9754-4d5b-9952-e5738bb14a60)