nineninesix/tyger

automatic-speech-recognition model by nineninesix

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TYGER TYGER - An open-weight speech decision model for real-time, full-duplex voice agents. It knows when to respond, keep listening, yield, and backchannel. tyger-s2s is our open-source voice agent built on this model (Apache-2.0). You talk to it in the browser, as on a phone call: when you cut in, and when to say "mm-hm"; and can be the voice backend of your own web app. To run the model in your own code, start from tyger-s2s's runtime (app/plugins/ears/tyger/). This repo holds weights and configs, no inference code. Guards: 6 warm-up frames, at least 350 ms of speech above -50 dB, 1.2 s between backchannels, and an endpoint after 1.2 s of silence even if the score stays low. The state input is LISTEN while the agent listens and SPEAK while it talks, never the model's own guess. The barge-in and backchannel defaults are looser than the evaluation's (0.93 and…

nineninesix/tyger on Hugging Face A short preview, not the full document.

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  10. Citation
  11. References

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Model overview

nineninesix/tyger is a automatic-speech-recognition model repository published by nineninesix on Hugging Face. A library was not reported.

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Model facts

Task
automatic-speech-recognition
Library
Not reported
Recent downloads (30 days)
589
Cumulative likes
90
Hugging Face trending score
81
Reported safetensors parameters
651,988,520
Architecture
TygerEndpointer
License
openmdw-1.1
Access
Not gated by Hugging Face
Created
2026-10-12T11:27:48.000Z
Last modified
2026-10-16T18:29:56.000Z

Compatibility and lineage

Reported languages: en

Reported base models: nvidia/nemotron-3.5-asr-streaming-0.6b

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.

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Source: Hugging Face Hub. Metadata observed 2026-10-24T06:45:27.935Z. Daily imports are snapshots, not real-time monitoring.

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