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README.md

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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 '@xenova/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.

onnx/decoder_model_merged.onnx

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