thoratsr7/whisper-base-onnx
By thoratsr7 · ↓ 11 · ♥ 0 · Updated 2026-03-21
What's in this repo
This page lists the files in thoratsr7/whisper-base-onnx, including whisper-base_beamsearch.int8.onnx, whisper-base_beamsearch.onnx.
- 2 ONNX models (.onnx files)
- 11 files, including 6 .json, 2 .onnx, 1 .md, 1 .txt
- Last updated 2026-03-21
ONNX files
| File | Size | Download |
|---|---|---|
| whisper-base_beamsearch.int8.onnx | — | Download |
| whisper-base_beamsearch.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
OpenAI Whisper base model converted to ONNX format for onnx-asr.
Install onnx-asr
pip install onnx-asr[cpu,hub]
Load whisper-base model and recognize wav file
import onnx_asr
model = onnx_asr.load_model("whisper-base")
print(model.recognize("test.wav")) # Auto-detect lang (slower)
print(model.recognize("test.wav", language="en"))
Model export
Read onnxruntime instruction for convert Whisper to ONNX.
Download model and export with Beam Search and Forced Decoder Input Ids:
python3 -m onnxruntime.transformers.models.whisper.convert_to_onnx -m openai/whisper-base --output ./whisper-onnx --use_forced_decoder_ids --optimize_onnx --precision fp32
Save tokenizer config
from transformers import WhisperTokenizer
processor = WhisperTokenizer.from_pretrained("openai/whisper-base")
processor.save_pretrained("whisper-onnx")
Model info
Created: 2026-03-21
Updated: 2026-03-21
View on Hugging Face