Di

Dia-Jax – A Jax port of the Dia text-to-speech dialogue model

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Dia-Jax – A Jax port of the Dia text-to-speech dialogue model

I've created a JAX port of Dia, the 1.6B parameter text-to-speech model that generates realistic dialogue from transcripts. This experimental port explores running Dia with JAX's functional paradigm and hardware flexibility potential. Key features: - Command-line interface for generating audio - Support for multi-speaker dialogue with [S1]/[S2] tags - Non-verbal sounds like (laughs), (coughs), etc. - Plans for voice cloning capability Current status: Functional but with memory optimization challenges. The PyTorch version can generate minutes of audio in <10GB VRAM, while this port currently has higher memory usage. Contributions from JAX optimization experts welcome! GitHub: [ https://github.com/jaco-bro/diajax ]

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Product HuntOn track for Day 1 leaderboard · Strong signals: model · Missing: mac, agents, macos
78%78% 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: created, para · Missing: supports, reddit linkedin, podcasting
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

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