🎤 whisper-base-onnx-web-v7

Fine-tuned Whisper model for Swedish transcription, optimized for web deployment with Transformers.js.

📋 Model Details

• Base Model: openai/whisper-base
• Language: Swedish (sv)
• Task: Speech Recognition / Transcription
• Training Steps: N/A
• License: MIT

🚀 Usage with Transformers.js

This model is optimized for browser-based transcription using Transformers.js:

import { pipeline } from '@xenova/transformers';

// Load the model
const transcriber = await pipeline(
  'automatic-speech-recognition',
  'markusingvarsson/whisper-base-onnx-web-v7'
);

// Transcribe audio
const result = await transcriber(audioFile, {
  language: 'sv',
  task: 'transcribe',
  chunk_length_s: 30,
  stride_length_s: 5
});

console.log(result.text);

🐍 Usage with Python

from transformers import pipeline

# Load pipeline
transcriber = pipeline(
    "automatic-speech-recognition",
    model="markusingvarsson/whisper-base-onnx-web-v7",
    device=0  # Use GPU if available
)

# Transcribe
result = transcriber(
    "audio.wav",
    generate_kwargs={"language": "sv", "task": "transcribe"}
)

print(result["text"])

📊 Performance

• Word Error Rate (WER): N/A%
• Model Size (ONNX): ~95MB (quantized)
• Inference Speed: 1-2x realtime on modern hardware

🎯 Intended Use

This model is designed for:

• Voice note transcription
• Meeting transcription
• Swedish podcast transcription
• Real-time speech-to-text in web browsers
• Accessibility applications

🔧 Training Details

• Hardware: GPU/CPU
• Batch Size: 8
• Learning Rate: 1e-5
• Training Loss: N/A

📁 Model Files

• *.onnx: ONNX model files for web deployment
• config.json: Model configuration
• tokenizer.json: Fast tokenizer for Transformers.js
• processor_config.json: Audio processing configuration

🌐 Demo

Try the model in your browser: [Coming Soon]

📝 Limitations

• Optimized for Swedish language only
• Best performance with clear audio (minimal background noise)
• May struggle with heavy dialects or very fast speech
• Maximum audio length: 30 seconds per chunk

🤝 Citation

If you use this model, please cite:

@misc{whisper_base_onnx_web_v7_2024,
  title={whisper-base-onnx-web-v7: Swedish Whisper for Web},
  author={markusingvarsson},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/markusingvarsson/whisper-base-onnx-web-v7}
}

🙏 Acknowledgments

• OpenAI for the original Whisper model
• Hugging Face for the tools and platform
• The Swedish NLP community

📄 License

This model is released under the MIT License.