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library_name: transformers.js
tags:
- transformers.js
- onnx
- whisper
pipeline_tag: automatic-speech-recognition
---
# Whisper Base ONNX
This is an ONNX conversion of OpenAI's [whisper-base](https://huggingface.co/openai/whisper-base) model, optimized for use with [Transformers.js](https://huggingface.co/docs/transformers.js).
## Model Details
- **Model Type:** Whisper (Encoder-Decoder)
- **Task:** Automatic Speech Recognition
- **Format:** ONNX (INT8 Quantized)
- **Size:** ~75MB (quantized from ~300MB)
## Usage
```javascript
import { pipeline } from '@huggingface/transformers';
const transcriber = await pipeline('automatic-speech-recognition', 'markusingvarsson/whisper-test');
const result = await transcriber('audio.wav');
console.log(result.text);
```
## Conversion Details
This model was converted using a custom conversion pipeline that:
1. Downloads the original HuggingFace model
2. Exports to ONNX format with KV caching
3. Applies INT8 quantization for smaller size
4. Adds Whisper-specific alignment heads for timestamp support
The quantized models are approximately 4x smaller than the original while maintaining accuracy.
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