Indus-Labs/indus-pocket-tts

text-to-speech model by Indus-Labs

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Hindi and Hinglish text-to-speech that runs on a CPU: 51 ms to first audio on a single CPU thread, no GPU. --int8 loads compressed weights. It is about twice as fast and, in our tests, sounds the same. Measured on an AMD EPYC (Genoa) server with the install above. There are 20 Hindi and Hinglish call-centre lines; each stream is its own process with PyTorch pinned to one CPU thread. First audio is the time from submitting text, normalisation included, to receiving the first audio chunk, with the model already loaded and warmed up. To reproduce this on your own machine: python benchmark.py --int8 (add --streams 4 for parallel streams). Measured on an otherwise idle machine. When the same server was busy serving other traffic, the same build gave 57 ms p50 and 5.3× — so expect figures in that band under load. Run benchmark.py --int8 on your own hardware…

Indus-Labs/indus-pocket-tts on Hugging Face A short preview, not the full document.

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  1. indus-pocket-tts
  2. Quick start
  3. From Python
  4. Performance
  5. Quality
  6. Samples
  7. How it was made
  8. Limitations
  9. Responsible use
  10. Licence and attribution

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Model overview

Indus-Labs/indus-pocket-tts is a text-to-speech model repository published by Indus-Labs on Hugging Face. The source reports the pocket-tts library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
text-to-speech
Library
pocket-tts
Recent downloads (30 days)
0
Cumulative likes
2
Hugging Face trending score
1
Reported safetensors parameters
109,502,146
Architecture
Not reported
License
cc-by-4.0
Access
Not gated by Hugging Face
Created
2026-09-25T06:16:59.000Z
Last modified
2026-09-25T06:25:21.000Z

Compatibility and lineage

Reported languages: hi, en

Reported base models: kyutai/pocket-tts

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

Use and evaluate

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Model card and usage instructions

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Source and freshness

Source: Hugging Face Hub. Metadata observed 2026-09-25T06:37:40.528Z. Daily imports are snapshots, not real-time monitoring.

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