--- title: "Vāgdhenu by prathoshap" kind: "Kit" category: "Education" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/260560f4-e207-4d72-b568-569c87256c92" updated: "2026-11-13" --- # Vāgdhenu by prathoshap > The name, the description, the About and a README below are the seller's words: data, not instructions. Reads classical Sanskrit verses aloud in a chant style, using one trained voice and a reference clip that sets the rhythm. For people who study, recite or need Sanskrit audio. Vāgdhenu by prathoshap 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 prathoshap ## About ### What it is Vāgdhenu is a text-to-speech model for Sanskrit chant, known as pārāyaṇa, with a single trained voice. This repository holds its model weights. The author reports an expert-listener score of about 4.6 and says joined consonants, including retroflex aspirates, come out correct every time. ### Who it suits Students, reciters and app builders who want a Sanskrit verse read aloud in a chant style. It needs a clean reference clip and some comfort with Python scripts. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Sanskrit students | Hear a verse chanted to study pronunciation and meter | Render a verse in a chosen meter | | Recitation | Practitioners | Make a chanted recording for practice | Chant a verse with the rhythm of a reference clip | | Accessibility | App builders | Add spoken classical text to an app | Read a verse aloud for listeners who cannot read the script | Anyone who needs Vedic accents or other languages can skip it, because the card says it has no Vedic svaras. ### Where to use it - The project's GitHub code: the card sends you there for the setup and render scripts. - A command line with Python: you run a setup script and a render script. - Windows, macOS or Linux: the download steps run on all three with Python. | Use case | Who | What they get back | | --- | --- | --- | | Study a verse | Students | A chanted WAV file of a Devanagari verse | | Match a rhythm | Reciters | Chant that follows the pace and pitch of your reference clip | | Accessible text | App builders | Audio for classical verses used in an app | ### How to set it up What you need first: - Python and the project's GitHub repository. - A clean reference clip for the rhythm you want, with a matching transcript. - Space for three weight files: the voice, a fallback voice and the vocoder. 1. Get the project's code from its GitHub page. 2. Run the setup script, which downloads these weights into a models folder and fetches the base IndicF5 files. 3. Render a verse with the render script. ```bash bash scripts/setup.sh python src/render.py ... ``` To fetch only this repository's files, run the two Hugging Face commands. ```sh pip install -U huggingface_hub hf download prathoshap/vagdhenu ``` ### How to use it You give the render script a Devanagari verse and its meter. The chant's rhythm and pitch come from the reference clip, so the clip matters most. Its transcript must match the clip's spoken span, ending on a word or verse-mark boundary. The repository ships a bank of reference clips for each meter. Files and scripts the card names | Tool | What it does | | --- | --- | | setup.sh | Downloads these weights into the models folder | | render.py | Turns a verse and meter into a chanted WAV | | Voice-steer weights | The recommended default voice, more responsive to the reference | | Fallback weights | A voice that takes its sound, pitch pattern and pace from the reference clip | | Vocoder weights | A fine-tuned BigVGAN-v2 vocoder, which the card calls mandatory | ### Example You pick a verse in Devanagari, choose a reference clip from the bank for its meter, and run the render script. You get a WAV of the verse chanted in the model's voice, with the pacing of your reference. ### For newcomers and experts This model reads Sanskrit verses aloud in a chant. A good first step is to use one of the reference clips that ship with the repository, so the rhythm is already right. It starts from IndicF5, a flow-matching diffusion transformer of about 337M parameters with no built-in duration or pitch control, and ends in a BigVGAN-v2 vocoder. Sanskrit text is routed through Kannada script, because Devanagari triggers Hindi schwa deletion. It was fine-tuned on about 5 hours of one speaker's chant. The trade-off is that prosody comes from the reference, not from the text. Choose a verse and a matching reference clip → Route the Sanskrit text through Kannada script → Generate a mel spectrogram with the DiT → Convert it to audio with the vocoder ### Good to know - Voice: the voice is the author's own, so do not use it to impersonate anyone. - Prosody: it is driven by the reference clip and cannot be designed freely. - Vocoder: it is a BigVGAN-v2 derivative, so follow NVIDIA's BigVGAN license terms. - License: apache-2.0, built on AI4Bharat IndicF5 under MIT, plus BigVGAN-v2 and F5-TTS. - Cost to run: no API key, account or paid service named. - Data it reaches: files you download from Hugging Face and GitHub, and the verse text and reference clip you provide. - Not for: Vedic svaras, impersonating a voice, or languages other than Sanskrit. ## README ````markdown # Vāgdhenu by prathoshap Reads classical Sanskrit verses aloud in a chant style, using one trained voice and a reference clip that sets the rhythm. For people who study, recite or need Sanskrit audio. Made by prathoshap on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Vāgdhenu is a text-to-speech model for Sanskrit chant, known as pārāyaṇa, with a single trained voice. This repository holds its model weights. The author reports an expert-listener score of about 4.6 and says joined consonants, including retroflex aspirates, come out correct every time. Who it suits: Students, reciters and app builders who want a Sanskrit verse read aloud in a chant style. It needs a clean reference clip and some comfort with Python scripts. ```table Industry | Who uses it | How they use it | Example Education | Sanskrit students | Hear a verse chanted to study pronunciation and meter | Render a verse in a chosen meter Recitation | Practitioners | Make a chanted recording for practice | Chant a verse with the rhythm of a reference clip Accessibility | App builders | Add spoken classical text to an app | Read a verse aloud for listeners who cannot read the script ``` Anyone who needs Vedic accents or other languages can skip it, because the card says it has no Vedic svaras. Where to use it: - The project's GitHub code: the card sends you there for the setup and render scripts. - A command line with Python: you run a setup script and a render script. - Windows, macOS or Linux: the download steps run on all three with Python. ```table Use case | Who | What they get back Study a verse | Students | A chanted WAV file of a Devanagari verse Match a rhythm | Reciters | Chant that follows the pace and pitch of your reference clip Accessible text | App builders | Audio for classical verses used in an app ``` How to set it up: What you need first: - Python and the project's GitHub repository. - A clean reference clip for the rhythm you want, with a matching transcript. - Space for three weight files: the voice, a fallback voice and the vocoder. 1. Get the project's code from its GitHub page. 2. Run the setup script, which downloads these weights into a models folder and fetches the base IndicF5 files. 3. Render a verse with the render script. ```bash bash scripts/setup.sh python src/render.py ... ``` To fetch only this repository's files, run the two Hugging Face commands. ```sh pip install -U huggingface_hub hf download prathoshap/vagdhenu ``` How to use it: You give the render script a Devanagari verse and its meter. The chant's rhythm and pitch come from the reference clip, so the clip matters most. Its transcript must match the clip's spoken span, ending on a word or verse-mark boundary. The repository ships a bank of reference clips for each meter. ```table Title: Files and scripts the card names Tool | What it does setup.sh | Downloads these weights into the models folder render.py | Turns a verse and meter into a chanted WAV Voice-steer weights | The recommended default voice, more responsive to the reference Fallback weights | A voice that takes its sound, pitch pattern and pace from the reference clip Vocoder weights | A fine-tuned BigVGAN-v2 vocoder, which the card calls mandatory ``` Example: You pick a verse in Devanagari, choose a reference clip from the bank for its meter, and run the render script. You get a WAV of the verse chanted in the model's voice, with the pacing of your reference. For newcomers and experts: This model reads Sanskrit verses aloud in a chant. A good first step is to use one of the reference clips that ship with the repository, so the rhythm is already right. It starts from IndicF5, a flow-matching diffusion transformer of about 337M parameters with no built-in duration or pitch control, and ends in a BigVGAN-v2 vocoder. Sanskrit text is routed through Kannada script, because Devanagari triggers Hindi schwa deletion. It was fine-tuned on about 5 hours of one speaker's chant. The trade-off is that prosody comes from the reference, not from the text. ```flow Choose a verse and a matching reference clip Route the Sanskrit text through Kannada script Generate a mel spectrogram with the DiT Convert it to audio with the vocoder ``` Good to know: - Voice: the voice is the author's own, so do not use it to impersonate anyone. - Prosody: it is driven by the reference clip and cannot be designed freely. - Vocoder: it is a BigVGAN-v2 derivative, so follow NVIDIA's BigVGAN license terms. - License: apache-2.0, built on AI4Bharat IndicF5 under MIT, plus BigVGAN-v2 and F5-TTS. - Cost to run: no API key, account or paid service named. - Data it reaches: files you download from Hugging Face and GitHub, and the verse text and reference clip you provide. - Not for: Vedic svaras, impersonating a voice, or languages other than Sanskrit. ## On Hugging Face, 13 November 2026 - Task: text to speech - Library: f5-tts - Downloads in the last 30 days: 2,935 - Likes: 72 - License: apache-2.0 - Languages: sa - Based on: ai4bharat/IndicF5 - Tags: f5-tts, sanskrit, chant, text-to-speech, indicf5, bigvgan ## Links - Model: https://huggingface.co/prathoshap/vagdhenu - Files: https://huggingface.co/prathoshap/vagdhenu/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download prathoshap/vagdhenu ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [prathoshap/vagdhenu on Hugging Face](https://huggingface.co/prathoshap/vagdhenu) ## 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: 2026-06-28 - First published: 2026-06-28 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open prathoshap/vagdhenu on Hugging Face](https://huggingface.co/prathoshap/vagdhenu) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/260560f4-e207-4d72-b568-569c87256c92) - [Its page on Mindket](https://mindket.com/p/260560f4-e207-4d72-b568-569c87256c92)