oruk/orukeet-r15-0100

Orukeet R15-0100

This repository preserves the original R15-0100 Orukeet checkpoint. The artifact is unchanged from the archived September 6, 2026 model. It has a FastConformer encoder and TDT decoder derived from NVIDIA Parakeet TDT 0.6B v3, with multilingual/accent adaptation and fitted temporal Gabor kernels materialized in the native weights.

The NeMo file is orukeet-r15-0100.nemo (2,509,342,720 bytes), SHA-256 4295a6d820a40b99786331d1c7a6b6c328916c8329b23d39415b0649a5d42811. Weights use CC BY-SA 4.0. Loading requires no custom model code:

from huggingface_hub import hf_hub_download
from nemo.collections.asr.models import ASRModel

path = hf_hub_download("oruk/orukeet-r15-0100", "orukeet-r15-0100.nemo", revision="073489c0619cd7939e327bebfc6c5d4ace4b69bf")
model = ASRModel.restore_from(path)

Training and evaluation history

R15-0100 precedes the later FT-4035 continuation whose training partitions were selected using an evaluation that included Monsoon English. It also precedes the later LibriSpeech test-other direct fine-tuning used to produce the released r3 checkpoint. Neither later stage is present in these weights.

Earlier evaluation and selection exposure remains. The original adaptation recipe included LibriSpeech test-other among validation/evaluation inputs, and the recovery selection leading to R15-0100 used a regression suite containing all 2,620 LibriSpeech test-clean recordings. Earlier VoxPopuli evaluation also occurred; its overlap with the current cleaned partition has not been established. The initial training recipe configured checkpoint monitoring, but the audit has not established whether test-other affected the particular fixed-step/EMA export inherited by R15-0100. Upstream pretraining overlap is not independently certified.

This model is an earlier checkpoint before the two later stages described above. Its earlier validation and selection exposure remains; it is not a fully unseen or held-out checkpoint. See the full disclosure and checkpoint provenance.