Instructions to use Hebrish/Sabich-Rolling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Hebrish/Sabich-Rolling with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Hebrish/Sabich-Rolling") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
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Sabich (Rolling) r1
Sabich (Rolling) is Sabich trained forward: each release continues
from the previous weights on all the recordings collected so far, instead of retraining from stock
nvidia/parakeet-tdt-0.6b-v2. It is the default model in the Hebrish apps from
2026-11-02 while it is tested; Sabich stays available.
English dictation with Hebrew (and some Yiddish) words dropped in, written in Latin letters, plus tech vocabulary, numbers and Israeli names. Same tokenizer, output style and usage as Sabich.
r1 (2026-11-02)
- Initialised from Sabich v2.4, continued for 6 epochs at learning rate 1e-5 on the full Sabich training blend (about 26 hours of audio), fresh optimizer, 10% public-English replay, last-5 checkpoint averaging.
- Checked internally against Sabich v2.4 on the same held-out sets before release.
Files
Sabich-Rolling.nemo: the NeMo model (ASRModel.restore_from("Sabich-Rolling.nemo")).Hebrish/Sabich-Rolling-sherpa-onnx-int8: int8 sherpa-onnx build used by the apps.
Contact: access@hebrish.app
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