Parkiet – Fine-tune a large TTS model for any language under $100

Hacker News

A lot of the open-source TTS models are released for English or Chinese and lack support for other languages. I was curious to see if I could train a state-of-the-art text-to-speech (TTS) model for Dutch by using Google's free TPU Research credits. The results are fantastic and on-par with ElevenLabs with just 10,000 hours of data. I open-sourced the weights, and documented the whole journey, from Torch model conversion, data preparation, JAX training code and inference pipeline. I spent about $300 in egress costs, but it can be as cheap as $100 to train this model (I ran the data collection pipeline on my 5090 Desktop PC as well as fine-tuning Whisper). Hopefully it can serve as a guide for others that are curious to train these models for other languages (without burning through all the credits trying to fix the pipeline).

Visit product View on Hacker NewsSep 24, 2025

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, models · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, 000 · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, para · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Fine-tune LLMs without catastrophic forgetting with CURLoRA approach44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine-tune LLMs without catastrophic forgetting with CURLoRA approach

Hacker News3

Fine-tune Llama3-8B on 8GB GPU without quantization42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine-tune Llama3-8B on 8GB GPU without quantization

Hacker News3

Fine Tune LLM's Without Code56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine Tune LLM's Without Code

Hacker News1

Pioneer70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine-tune any LLM in minutes, with one prompt

Product Hunt+115API

Streamtune - Fine-Tune LLMs with Zero Code54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Streamtune - Fine-Tune LLMs with Zero Code

Hacker News1

I built a simple UI to create fine tune GPT 3.5 model45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a simple UI to create fine tune GPT 3.5 model

Hacker News2

Fine-tune llama3 model to support function calling51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine-tune llama3 model to support function calling

Hacker News3

LlamaGym – fine-tune LLM agents with online reinforcement learning34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LlamaGym – fine-tune LLM agents with online reinforcement learning

Hacker News239

TuneTrain.ai78%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fine-tune AI models with your augmented data

Product Hunt+79SaaS

Writekin – fine-tune a local LLM on your own writing, on your Mac26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Writekin – fine-tune a local LLM on your own writing, on your Mac

Hacker News6

Browse all products Analyze your launch