All builds for this model:

X-ASR-zh-en is a compact bilingual (Chinese + English) streaming speech-recognition model from GilgameshWind, built with the icefall / k2 recipe as a cache-aware Zipformer2 RNN-T transducer (a 6-stack, 19-layer Zipformer2 encoder, a stateless RNN-T decoder, and a tanh joiner over a 5000-token BPE vocabulary, ~0.16B parameters). The same checkpoint serves both low-latency streaming captions and full-file offline transcription, making it a good fit for on-device Chinese/English dictation and real-time subtitles. This OpenASR repo repackages the weights as .oasr packs that run natively in the OpenASR runtime — no Python at inference time, all decoding local. The q8_0 build is the recommended default (it matched the fp16 transcript bit-for-bit in OpenASR's verification); q4_k is the smallest build for tight-memory devices and fp16 is for maximum fidelity or verification.

Converted from GilgameshWind/X-ASR-zh-en with the OpenASR importer:

The .oasr container is GGUF-backed; packs use zero-copy mmap weight binding and graph buffer reuse to keep peak memory low.

These packs inherit the upstream model's license: Apache-2.0 (source). OpenASR packaging retains the upstream copyright and NOTICE; the only modifications are format conversion and quantization.

This pack is a redistribution of X-ASR-zh-en, created and open-sourced by GilgameshWind (GilgameshWind/X-ASR-zh-en). All credit for the original architecture, training, and weights belongs to the author; the license is inherited from and identical to the upstream model (Apache-2.0). The model is built on the icefall / k2 / Next-gen Kaldi Zipformer2 transducer recipe — thank you to the icefall team and to GilgameshWind for releasing their work openly. OpenASR only performs format conversion, quantization, runtime verification, and local-inference adaptation.