40 lines
1.5 KiB
Markdown
40 lines
1.5 KiB
Markdown
# Local Model Setup
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Linnet runs fully locally on the Free tier. The transcription pipeline (Whisper) and tone annotation engine (wav2vec2-based SER, or speech emotion recognition) are bundled and download automatically on first start. No additional setup is required for core functionality.
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## What runs locally
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| Component | Model | Purpose |
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|-----------|-------|---------|
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| Transcription | Whisper (base or small) | Speech-to-text |
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| Tone annotation | wav2vec2 SER | Emotional/social register classification |
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Audio never leaves your machine. Both models run on-device via the `cf-voice` inference layer.
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## Optional: translation via DeepL
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Translation is the only feature that requires an external service. Two paths are available:
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### Free tier: BYOK (bring your own key)
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[DeepL offers a free API tier](https://www.deepl.com/en/pro/change-plan) (500,000 characters/month). Sign up, copy your API key, and add it to your `.env`:
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```dotenv
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DEEPL_API_KEY=your-deepl-api-key-here
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```
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Restart Linnet after saving the file.
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### Paid tier
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The Paid tier includes a CF-managed DeepL key. No environment variable is needed. Translation appears automatically once your license key is active.
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## Choosing a Whisper model size
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The default is `whisper-base`. If your machine has more VRAM or you want higher accuracy:
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```dotenv
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WHISPER_MODEL=small # default: base
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```
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Available sizes: `tiny`, `base`, `small`, `medium`, `large`. Larger models are slower but more accurate, especially for accented speech.
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