metadata
license: apache-2.0
language:
- id
- ind
tags:
- automatic-speech-recognition
- onnx
- onnx-asr
- whisper
- indonesian
base_model: cahya/whisper-medium-id
whisper-medium-id — ONNX
ONNX export of cahya/whisper-medium-id
(Whisper medium fine-tuned for Indonesian by cahya) for
onnx-asr (standard whisper model type — works with
stock onnx-asr, no patches needed). fp32 and int8 variants included.
License: apache-2.0, inherited from the source model.
Usage
import onnx_asr
model = onnx_asr.load_model("whisper", "path/to/this/repo") # or quantization="int8"
print(model.recognize("audio_16khz.wav", language="id"))
Verified on a FLEURS Indonesian (id_id) test clip:
- Reference: "tim-tim virtual memiliki standar keunggulan yang sama dengan tim konvensional tetapi ada sedikit perbedaan"
- fp32: "Tim-tim virtual memiliki standar keunggulan yang sama dengan tim konvensional, tetapi ada sedikit perbedaan." (RTF 0.87)
- int8: identical transcript (RTF 0.34)
Both exact matches to the reference (modulo punctuation/casing). RTF measured on an AMD Ryzen 5 7600 (CPU, 4 OMP threads, shared/loaded box — not a clean benchmark number).
Int8 decoder was produced by quantizing the pre-merge decoders separately and re-merging
(merge_decoders(..., strict=False)); direct quantization of the merged decoder graph does
not shrink it (its If subgraphs are skipped by onnxruntime's dynamic quantizer).