--- title: "F5-TTS" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/891bef85-1e3d-4472-903f-1f320f92bc4b" updated: "2026-11-13" --- # F5-TTS > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns text into speech with the F5-TTS flow-matching model, shipped as F5-TTS and E2 TTS base checkpoints. For developers and researchers working under a non-commercial license. F5-TTS is a kit in the Developer 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 SWivid ## About ### What it is F5-TTS is a text-to-speech model published by SWivid, and this repository holds its base checkpoints. It also carries a base checkpoint of E2 TTS. The linked paper describes the method as flow matching. The README gives no description of the model beyond the checkpoint layout, so this page stays short. ### Who it suits It suits speech researchers and developers who want public text-to-speech weights for non-commercial work. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Speech researchers | Start from the published base checkpoints and the paper | Loading a base checkpoint to study its output | | Software | Hobby developers | Add speech output to a personal project | A narration feature in a side project | | Education | Students | Study how a public text-to-speech model is packaged | Setting up the checkpoint folder from scratch | You can skip it if you need commercial use, because the license is CC BY-NC 4.0. ### Where to use it - Python, using the f5-tts library - Windows, macOS or Linux, once the files are downloaded | Use case | Who | What they get back | | --- | --- | --- | | Speech research | Researchers | Base checkpoints to start from | | Personal projects | Developers | Spoken audio from written text | | Model comparison | Students | F5-TTS and E2 TTS checkpoints side by side | ### How to set it up - Python, to run the Hugging Face download tool - The huggingface\_hub package - The f5-tts library, which the project's own page describes 1. Install the Hugging Face hub package. 2. Download the repository files to your computer. 3. Place each checkpoint under a ckpts folder, in the layout shown below. ```sh pip install -U huggingface_hub hf download SWivid/F5-TTS ``` The card shows this folder layout for the checkpoints. ```text ckpts/ F5TTS_v1_Base/ model_1250000.safetensors F5TTS_Base/ model_1200000.safetensors E2TTS_Base/ model_1200000.safetensors ``` ### How to use it The README shows no run command. It gives the checkpoint layout and points to the project's GitHub page and paper, so follow the project's own instructions to turn text into speech. | Tool | What it does | | --- | --- | | hf download | Fetches the checkpoint files to your computer | | ckpts folder | Where the project expects the checkpoint files | | F5TTS\_v1\_Base | The v1 base checkpoint of F5-TTS | | F5TTS\_Base | The base checkpoint of F5-TTS | | E2TTS\_Base | The base checkpoint of E2 TTS | ### Example You download the repository, put the F5TTS\_v1\_Base checkpoint in its folder under ckpts, and follow the project's instructions to speak a sentence. You get audio of that sentence back. ### For newcomers and experts Text to speech turns written words into spoken audio. To start, download the files and arrange the ckpts folder exactly as shown, then read the project's instructions. If you know the field, the paper frames F5-TTS around flow matching, and the repository stores three base checkpoints as Safetensors files named by training step. The README gives no training data or benchmarks, and the license excludes commercial use. You download a base checkpoint → You place it under the ckpts folder → The f5-tts library loads it → Your text becomes speech ### Good to know - Checkpoints: F5-TTS v1 base, F5-TTS base and E2 TTS base - Variants: Hugging Face lists 8 quantized and 154 fine-tuned versions made by other people - License: CC BY-NC 4.0 - Cost to run: none named - Data it reaches: the text you give it, and the files you download from Hugging Face - Not for: commercial use, since the license is non-commercial ## README ````markdown # F5-TTS Turns text into speech with the F5-TTS flow-matching model, shipped as F5-TTS and E2 TTS base checkpoints. For developers and researchers working under a non-commercial license. Made by SWivid 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: F5-TTS is a text-to-speech model published by SWivid, and this repository holds its base checkpoints. It also carries a base checkpoint of E2 TTS. The linked paper describes the method as flow matching. The README gives no description of the model beyond the checkpoint layout, so this page stays short. Who it suits: It suits speech researchers and developers who want public text-to-speech weights for non-commercial work. ```table Industry | Who uses it | How they use it | Example Research | Speech researchers | Start from the published base checkpoints and the paper | Loading a base checkpoint to study its output Software | Hobby developers | Add speech output to a personal project | A narration feature in a side project Education | Students | Study how a public text-to-speech model is packaged | Setting up the checkpoint folder from scratch ``` You can skip it if you need commercial use, because the license is CC BY-NC 4.0. Where to use it: - Python, using the f5-tts library - Windows, macOS or Linux, once the files are downloaded ```table Use case | Who | What they get back Speech research | Researchers | Base checkpoints to start from Personal projects | Developers | Spoken audio from written text Model comparison | Students | F5-TTS and E2 TTS checkpoints side by side ``` How to set it up: - Python, to run the Hugging Face download tool - The huggingface_hub package - The f5-tts library, which the project's own page describes 1. Install the Hugging Face hub package. 2. Download the repository files to your computer. 3. Place each checkpoint under a ckpts folder, in the layout shown below. ```sh pip install -U huggingface_hub hf download SWivid/F5-TTS ``` The card shows this folder layout for the checkpoints. ```text ckpts/ F5TTS_v1_Base/ model_1250000.safetensors F5TTS_Base/ model_1200000.safetensors E2TTS_Base/ model_1200000.safetensors ``` How to use it: The README shows no run command. It gives the checkpoint layout and points to the project's GitHub page and paper, so follow the project's own instructions to turn text into speech. ```table Tool | What it does hf download | Fetches the checkpoint files to your computer ckpts folder | Where the project expects the checkpoint files F5TTS_v1_Base | The v1 base checkpoint of F5-TTS F5TTS_Base | The base checkpoint of F5-TTS E2TTS_Base | The base checkpoint of E2 TTS ``` Example: You download the repository, put the F5TTS_v1_Base checkpoint in its folder under ckpts, and follow the project's instructions to speak a sentence. You get audio of that sentence back. For newcomers and experts: Text to speech turns written words into spoken audio. To start, download the files and arrange the ckpts folder exactly as shown, then read the project's instructions. If you know the field, the paper frames F5-TTS around flow matching, and the repository stores three base checkpoints as Safetensors files named by training step. The README gives no training data or benchmarks, and the license excludes commercial use. ```flow You download a base checkpoint You place it under the ckpts folder The f5-tts library loads it Your text becomes speech ``` Good to know: - Checkpoints: F5-TTS v1 base, F5-TTS base and E2 TTS base - Variants: Hugging Face lists 8 quantized and 154 fine-tuned versions made by other people - License: CC BY-NC 4.0 - Cost to run: none named - Data it reaches: the text you give it, and the files you download from Hugging Face - Not for: commercial use, since the license is non-commercial ## On Hugging Face, 13 November 2026 - Task: text to speech - Library: f5-tts - Downloads in the last 30 days: 1,335,845 - Likes: 1,230 - License: cc-by-nc-4.0 - Quantized versions: 8 - Fine-tunes: 155 - Tags: f5-tts, text-to-speech ## Links - Model: https://huggingface.co/SWivid/F5-TTS - Files: https://huggingface.co/SWivid/F5-TTS/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download SWivid/F5-TTS ``` Then follow the usage in its model card. 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 [SWivid/F5-TTS on Hugging Face](https://huggingface.co/SWivid/F5-TTS) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | F5-TTS (this page) | 1,335,845 | 1,230 | — | cc-by-nc-4.0 | 2025-03-21 | | [Kokoro-82M](https://mindket.com/p/a2267d0b-49dd-4503-a35b-5f8a4280e116) | 12,580,963 | 7,403 | — | apache-2.0 | 2025-04-10 | | [Chatterbox TTS](https://mindket.com/p/4681ce24-a293-418d-9c0e-991b1a7d6e7f) | 2,440,902 | 1,911 | — | mit | 2026-06-10 | | [VieNeu-TTS v3 Turbo](https://mindket.com/p/1dc8a3b8-2ee4-414e-bca9-d273eb678fee) | 2,151,800 | 109 | 131M | apache-2.0 | 2026-09-23 | | [Qwen3-TTS GGUF](https://mindket.com/p/ab5107b1-bdce-42f1-b3e2-abd1bae80d7c) | 1,347,066 | 67 | 915M | apache-2.0 | 2026-09-09 | | [VoxCPM2](https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e) | 984,860 | 1,783 | 2.3B | apache-2.0 | 2026-11-09 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · sandreas · 2025-08-06](https://news.ycombinator.com/item?id=44807307): Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model: Cool. While I think this is indeed impressive and has a specific use case (e.g. in the embedded sector), I'm not totally convinced that the quality is good enough to replace bigger models. With fish-speech1 and f5-tts2 there are at least 2 open source models pushing the quality limits of… - [Bluesky · Neil Crump · 2026-04-12](https://bsky.app/profile/pyramidhead76.bsky.social/post/3mjdbwwaz5c26): when I first used it it would sometimes crash with longer strings, but this uncommitted PR fixed it- github.com/SWivid/F5-TT... But basically, upload up to 12 seconds of sample audio and it'll then produce any length of text in that voice. - [Hacker News · thorsten-voice · 2024-11-12](https://news.ycombinator.com/item?id=42119151): A CC-By Open-Source TTS Model with Voice Cloning: You're very welcome. On f5 github repo is an active discussion (i'm involved too) on supporting other languages including german: https://github.com/SWivid/F5-TTS/issues/87\#issuecomment-2418... - [Bluesky · Neil Crump · 2026-04-12](https://bsky.app/profile/pyramidhead76.bsky.social/post/3mjdaapnrp22z): I also had a play with github.com/swivid/f5-tts the other day, which is VERY impressive if slightly creepy. - [Hacker News · terhechte · 2024-10-28](https://news.ycombinator.com/item?id=41968590): NotebookLlama: An open source version of NotebookLM: I tried to build something kind of like NotebookLM (personalized news podcasts) over the past months (https://www.tailoredpod.ai), but biggest issue is that the existing good TTS Apis are so expensive that a product such as NotebookLM is not really possible for a normal company that doesn't have… - [Bluesky · 土豆哥 · 2026-07-26](https://bsky.app/profile/anotherbug.com/post/3mrkqrmes3y2n): 想跑语音/音频类 AI，这 4 个开源项目今天就能直接用： 1. Whisper，OpenAI 的语音识别 github.com/openai/whisper 2. F5-TTS，文本转语音 github.com/SWivid/F5-TTS 3. Coqui TTS，文本转语音 github.com/coqui-ai/TTS 4. RVC，变声/音色转换 github.com/RVC-Project... 都是开源，本地能跑。 - [Hacker News · mlboss · 2024-10-14](https://news.ycombinator.com/item?id=41843344): Play 3.0 mini – A lightweight, reliable, cost-efficient Multilingual TTS model: On related note a very good open source TTS model was released 2 days back: https://github.com/SWivid/F5-TTS Very good voice cloning capability. Runs under 10G vram nvidia gpu. - [Bluesky · EUVD Bot · 2026-06-01](https://bsky.app/profile/euvd-bot.bsky.social/post/3mnaum7j4wr2u): 🚨 EUVD-2026-33744 📊 8.8/10 🏢 SWivid 📝 F5-TTS through version 1.1.20 contains a path traversal vulnerability in the finetune Gradio handlers that allows unauthenticated attackers to write arbitr... 🔗 https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-33744 \#cybersecurity \#infosec \#cve \#euvd - [Hacker News · diggan · 2024-10-14](https://news.ycombinator.com/item?id=41842281): Play 3.0 mini – A lightweight, reliable, cost-efficient Multilingual TTS model: I was literally just looking at that today, and the best one I came across was F5-TTS: https://swivid.github.io/F5-TTS/ Only thing missing (for me) is "emotion tokens" instead of forcing the entire generation to be with a specific emotion, as the generated voice is a bit too robotic otherwise. - [Bluesky · Tom Dörr · 2026-04-20](https://bsky.app/profile/tom-doerr.bsky.social/post/3mjxbg5vmlg2a): https://github.com/SWivid/F5-TTS - [Hacker News · popalchemist · 2024-10-14](https://news.ycombinator.com/item?id=41840640): Notable AI Models: The trends around compute increasing is on the whole correct but by no means is it a universal rule. More optimized training procedures and model architectures are coming out all the time. In just the last week, we got F5-TTS which is trained on twice as much data as the previous leader in… - [Hacker News · modeless · 2024-10-13](https://news.ycombinator.com/item?id=41824747): Omni SenseVoice: High-Speed Speech Recognition with Words Timestamps: Looks cool\! Combine this with this new TTS that released today that looks really good and an LLM and you'd have a pretty good all-local voice assistant\! https://github.com/SWivid/F5-TTS ## 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: 2025-03-21 - First published: 2024-10-07 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open SWivid/F5-TTS on Hugging Face](https://huggingface.co/SWivid/F5-TTS) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/891bef85-1e3d-4472-903f-1f320f92bc4b) - [Its page on Mindket](https://mindket.com/p/891bef85-1e3d-4472-903f-1f320f92bc4b)