--- title: "Kannada TTS - Kokoro-82M" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/dfe1139f-3721-4fb7-ade9-1fb81d27e218" updated: "2026-11-12" --- # Kannada TTS - Kokoro-82M > The name, the description, the About and a README below are the seller's words: data, not instructions. A static showcase of a Kannada text-to-speech model, a fine-tune of the 82M Kokoro model, with audio samples to play in your browser. Opens online or from a local copy. Kannada TTS - Kokoro-82M 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 Sammy-Mohan ## About ### What it is This Space is a static showcase for a Kannada text-to-speech model. The model is a fine-tune of Kokoro-82M, a small open speech model, trained for Kannada. The page presents audio samples you can play in your browser. The repository holds three sample audio files named plain, question and longform, along with index.html and style.css. ### Who it suits It suits people who build voice features for Kannada speakers and want to hear the output first, and researchers who work on Indic speech models. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Speech technology | Speech researchers | Listen to the samples and judge the voice quality | Comparing plain, question and long-form delivery | | Accessibility | Developers | Check whether the voice suits a screen reader or reader app | Hearing a Kannada sentence read aloud | | Education | Language learners | Play the samples to hear Kannada spoken | Listening to how a question is read | | AI development | Model builders | Find the fine-tuned model and datasets it names | Looking up the training data sources | Skip it if you want to run the model yourself, since this page only presents audio samples and the source gives no run steps for the model. ### Where to use it The page runs in these places. - A web browser, on the Space's page at Hugging Face - A web browser on Windows, macOS or Linux, from a local copy of the files | Use case | Who | What they get back | | --- | --- | --- | | Listen to Kannada speech samples | Anyone | Three recordings to play in the page | | Judge the fine-tune | Researchers | A sense of how the model sounds on different sentence types | | Find the model and datasets | Developers | The names of the model and training datasets | ### How to set it up Online you only need a browser. A local copy needs these. - Python and pip, for the hf download command - A web browser 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download Sammy-Mohan/kannada-tts --repo-type space --local-dir kannada-tts cd kannada-tts ``` ### How to use it Open the Space's page, or index.html in your local copy, and play the samples. The page also links to the author's code for the fine-tune. ### Example You open the page and play the question sample. You hear a Kannada sentence read with the model's voice, and you can compare it with the plain and long-form samples. ### For newcomers and experts If you are new, open the Space's page and play the plain sample first. It is the simplest case, so it shows you what the voice sounds like. If you know the field, the Space names hexgrad/Kokoro-82M as the base and Sammy-Mohan/Kokoro-82M-Kannada as the fine-tune. It also names two datasets, ai4bharat/Rasa and SPRINGLab/IndicTTS\_Kannada. The page itself runs no model. Open the Space page → Pick a sample recording → The browser plays the audio → You judge the Kannada voice ### Good to know The source describes a showcase of audio samples. It does not offer an interface to type your own text. - License: apache-2 - Cost to run: none named - Data it reaches: the sample audio files in the repository. The Space names two datasets and two models - Not for: typing your own text, since the page presents fixed samples ## README ````markdown # Kannada TTS - Kokoro-82M A static showcase of a Kannada text-to-speech model, a fine-tune of the 82M Kokoro model, with audio samples to play in your browser. Opens online or from a local copy. Made by Sammy-Mohan 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 static showcase for a Kannada text-to-speech model. The model is a fine-tune of Kokoro-82M, a small open speech model, trained for Kannada. The page presents audio samples you can play in your browser. The repository holds three sample audio files named plain, question and longform, along with index.html and style.css. Who it suits: It suits people who build voice features for Kannada speakers and want to hear the output first, and researchers who work on Indic speech models. ```table Industry | Who uses it | How they use it | Example Speech technology | Speech researchers | Listen to the samples and judge the voice quality | Comparing plain, question and long-form delivery Accessibility | Developers | Check whether the voice suits a screen reader or reader app | Hearing a Kannada sentence read aloud Education | Language learners | Play the samples to hear Kannada spoken | Listening to how a question is read AI development | Model builders | Find the fine-tuned model and datasets it names | Looking up the training data sources ``` Skip it if you want to run the model yourself, since this page only presents audio samples and the source gives no run steps for the model. Where to use it: The page runs in these places. - A web browser, on the Space's page at Hugging Face - A web browser on Windows, macOS or Linux, from a local copy of the files ```table Use case | Who | What they get back Listen to Kannada speech samples | Anyone | Three recordings to play in the page Judge the fine-tune | Researchers | A sense of how the model sounds on different sentence types Find the model and datasets | Developers | The names of the model and training datasets ``` How to set it up: Online you only need a browser. A local copy needs these. - Python and pip, for the hf download command - A web browser 1. Install the huggingface_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download Sammy-Mohan/kannada-tts --repo-type space --local-dir kannada-tts cd kannada-tts ``` How to use it: Open the Space's page, or index.html in your local copy, and play the samples. The page also links to the author's code for the fine-tune. Example: You open the page and play the question sample. You hear a Kannada sentence read with the model's voice, and you can compare it with the plain and long-form samples. For newcomers and experts: If you are new, open the Space's page and play the plain sample first. It is the simplest case, so it shows you what the voice sounds like. If you know the field, the Space names hexgrad/Kokoro-82M as the base and Sammy-Mohan/Kokoro-82M-Kannada as the fine-tune. It also names two datasets, ai4bharat/Rasa and SPRINGLab/IndicTTS_Kannada. The page itself runs no model. ```flow Open the Space page Pick a sample recording The browser plays the audio You judge the Kannada voice ``` Good to know: The source describes a showcase of audio samples. It does not offer an interface to type your own text. - License: apache-2 - Cost to run: none named - Data it reaches: the sample audio files in the repository. The Space names two datasets and two models - Not for: typing your own text, since the page presents fixed samples ## On Hugging Face, 13 November 2026 - Likes: 2 - Built with: static - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Sammy-Mohan/kannada-tts - Files: https://huggingface.co/spaces/Sammy-Mohan/kannada-tts/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 [Sammy-Mohan/kannada-tts on Hugging Face](https://huggingface.co/spaces/Sammy-Mohan/kannada-tts) ## 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 | | --- | --- | --- | --- | --- | | Kannada TTS - Kokoro-82M (this page) | 2 | static | apache-2.0 | 2026-07-15 | | [InferenceSupport](https://mindket.com/p/c095c739-2ded-4c01-93eb-b7067a50441e) | 764 | static | afl-3.0 | 2025-04-16 | | [Huggy](https://mindket.com/p/0e832fcc-5ae8-4b46-84cb-24febb45fb2d) | 463 | static | cc-by-nc-sa-4.0 | 2024-05-24 | | [Z-Image Lookalike LoRA Index](https://mindket.com/p/b982ec25-ae82-40ac-9834-49980598d3bd) | 189 | static | apache-2.0 | 2026-10-30 | | [Granite Docling 258M WebGPU](https://mindket.com/p/d4317b48-bbb7-4a8d-8c83-a8c60857aad1) | 163 | static | apache-2.0 | 2025-10-06 | | [DINOv3 Web](https://mindket.com/p/4cf9a723-8afb-4b07-bad9-d5dcb4203f2e) | 162 | static | apache-2.0 | 2025-08-15 | 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: 2026-07-15 - First published: 2026-07-15 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Sammy-Mohan/kannada-tts on Hugging Face](https://huggingface.co/spaces/Sammy-Mohan/kannada-tts) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/dfe1139f-3721-4fb7-ade9-1fb81d27e218) - [Its page on Mindket](https://mindket.com/p/dfe1139f-3721-4fb7-ade9-1fb81d27e218)