Transcription: dwindle model choice to Whisper Base + Whisper Large v3
Registry now lists exactly two models instead of five:
- 'Whisper Base' — names the actual bundled model (was 'Base (default)').
- 'Whisper Large v3' — kept; honest copy on size/speed/RAM.
tiny/small/medium removed from the registry (validate_model_name now
rejects them; existing rows keep their saved model — all current data
is 'base', still valid).
Detail screen shows the model that WILL run by real display name
('Whisper Base (default)') instead of 'Use default (base)'; the picker
lists the two models with the default marked inline.
Backend 78 passed/1 skipped; app 34/34; engine hot-reloaded clean.
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parent
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4 changed files with 43 additions and 64 deletions
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@ -37,42 +37,20 @@ class TranscriptionModelInfo:
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SUPPORTED_TRANSCRIPTION_MODELS: dict[str, TranscriptionModelInfo] = {
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"tiny": TranscriptionModelInfo(
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name="tiny",
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display_name="Tiny",
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description="Fastest and lightest. Good for quick drafts and slow machines.",
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params="~39M",
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approx_memory="~1 GB RAM",
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relative_speed="~10x real-time (CPU)",
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),
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"base": TranscriptionModelInfo(
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name="base",
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display_name="Base (default)",
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description="Balanced default. Works reasonably well on ordinary computers.",
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display_name="Whisper Base",
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description="The bundled model — works offline out of the box. "
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"Good for clear speech on ordinary computers.",
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params="~74M",
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approx_memory="~1 GB RAM",
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relative_speed="~7x real-time (CPU)",
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),
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"small": TranscriptionModelInfo(
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name="small",
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display_name="Small",
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description="Better accuracy with higher resource usage.",
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params="~244M",
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approx_memory="~2 GB RAM",
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relative_speed="~4x real-time (CPU)",
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),
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"medium": TranscriptionModelInfo(
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name="medium",
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display_name="Medium",
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description="Higher accuracy and slower performance.",
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params="~769M",
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approx_memory="~5 GB RAM",
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relative_speed="~2x real-time (CPU)",
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),
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"large-v3": TranscriptionModelInfo(
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name="large-v3",
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display_name="Large v3",
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description="Highest accuracy and greatest resource requirements.",
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display_name="Whisper Large v3",
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description="Best accuracy (accents, names, messy audio). Downloads "
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"~3 GB once; slow on CPU — best on machines with 16 GB+ RAM.",
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params="~1.5B",
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approx_memory="~10 GB RAM",
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relative_speed="~1x real-time (CPU)",
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