| { |
| "_about": "Read by the Transcriber app (Check for updates). models: as transcriber/catalog.json, used when revision is higher than the app's own. app: the latest version and its installer.", |
| "revision": 2, |
| "models": [ |
| { |
| "id": "gpu-support", |
| "kind": "gpu", |
| "name": "GPU support (NVIDIA cuBLAS and cuDNN)", |
| "about": "Lets the speech models run on your NVIDIA graphics card, many times faster than on the processor. Shown only on computers with an NVIDIA card.", |
| "languages": "Any", |
| "license": "NVIDIA software licence", |
| "size_mb": 1373, |
| "download_mb": 1373, |
| "source": { |
| "pypi": true |
| } |
| }, |
| { |
| "id": "large-v3", |
| "kind": "speech", |
| "name": "Best accuracy (Whisper large-v3)", |
| "about": "The most accurate general model. Best with an NVIDIA graphics card.", |
| "languages": "99 languages", |
| "license": "MIT", |
| "size_mb": 3091, |
| "cost": 1.0, |
| "vram_gb": 5, |
| "source": { |
| "repo": "Systran/faster-whisper-large-v3" |
| } |
| }, |
| { |
| "id": "large-v3-turbo", |
| "kind": "speech", |
| "name": "Fast and accurate (Whisper large-v3 turbo)", |
| "about": "Nearly as accurate as large-v3 and several times faster. A good choice without a powerful graphics card.", |
| "languages": "99 languages", |
| "license": "MIT", |
| "size_mb": 1622, |
| "cost": 0.3, |
| "vram_gb": 3, |
| "source": { |
| "repo": "mobiuslabsgmbh/faster-whisper-large-v3-turbo" |
| } |
| }, |
| { |
| "id": "distil-large-v3", |
| "kind": "speech", |
| "name": "Fast, English only (Distil-Whisper large-v3)", |
| "about": "Close to large-v3 accuracy on English, much faster. English recordings only.", |
| "languages": "English", |
| "license": "MIT", |
| "size_mb": 1516, |
| "cost": 0.3, |
| "vram_gb": 3, |
| "source": { |
| "repo": "Systran/faster-distil-whisper-large-v3" |
| } |
| }, |
| { |
| "id": "medium", |
| "kind": "speech", |
| "name": "Medium (Whisper medium)", |
| "about": "Smaller and faster than large, a little less accurate.", |
| "languages": "99 languages", |
| "license": "MIT", |
| "size_mb": 1531, |
| "cost": 0.5, |
| "vram_gb": 2.5, |
| "source": { |
| "repo": "Systran/faster-whisper-medium" |
| } |
| }, |
| { |
| "id": "small", |
| "kind": "speech", |
| "name": "Small (Whisper small)", |
| "about": "Quick on any computer; fine for clear recordings, weaker on accents and noise.", |
| "languages": "99 languages", |
| "license": "MIT", |
| "size_mb": 486, |
| "cost": 0.2, |
| "vram_gb": 1, |
| "source": { |
| "repo": "Systran/faster-whisper-small" |
| } |
| }, |
| { |
| "id": "base", |
| "kind": "speech", |
| "name": "Base (Whisper base)", |
| "about": "Very fast, rough drafts only.", |
| "languages": "99 languages", |
| "license": "MIT", |
| "size_mb": 148, |
| "cost": 0.08, |
| "vram_gb": 0.5, |
| "source": { |
| "repo": "Systran/faster-whisper-base" |
| } |
| }, |
| { |
| "id": "ivrit-large-v3-turbo", |
| "kind": "speech", |
| "name": "Hebrew, fast (ivrit.ai large-v3 turbo)", |
| "about": "Whisper trained further on Hebrew by ivrit.ai: much better Hebrew than the general models.", |
| "languages": "Hebrew (and English)", |
| "license": "Apache-2.0", |
| "size_mb": 1622, |
| "cost": 0.3, |
| "vram_gb": 3, |
| "source": { |
| "repo": "ivrit-ai/whisper-large-v3-turbo-ct2" |
| } |
| }, |
| { |
| "id": "ivrit-large-v3", |
| "kind": "speech", |
| "name": "Hebrew, best (ivrit.ai large-v3)", |
| "about": "The most accurate Hebrew model from ivrit.ai. Best with an NVIDIA graphics card.", |
| "languages": "Hebrew (and English)", |
| "license": "Apache-2.0", |
| "size_mb": 3091, |
| "cost": 1.0, |
| "vram_gb": 5, |
| "source": { |
| "repo": "ivrit-ai/whisper-large-v3-ct2" |
| } |
| }, |
| { |
| "id": "ecapa", |
| "kind": "voice", |
| "name": "Speaker recognition (SpeechBrain ECAPA, ONNX)", |
| "about": "Tells the voices apart. Needed for every transcription.", |
| "languages": "Any", |
| "license": "Apache-2.0", |
| "size_mb": 84, |
| "required": true, |
| "files": [ |
| "ecapa-any-length.onnx" |
| ], |
| "source": { |
| "repo": "kenrunio/transcriber-speaker-onnx" |
| }, |
| "sha256": { |
| "ecapa-any-length.onnx": "700b63064ee98981186f59f247d28e56f7f6ab265d8b50ebb450db5a8ce21dc7" |
| } |
| }, |
| { |
| "id": "punctuation", |
| "kind": "punctuation", |
| "name": "Punctuation repair (fullstop multilang large, ONNX, 8-bit)", |
| "about": "Adds full stops and commas where Whisper leaves run-on text. Optional; English, German, French and Italian.", |
| "languages": "English, German, French, Italian", |
| "license": "MIT", |
| "size_mb": 581, |
| "files": [ |
| "model_int8.onnx", |
| "tokenizer.json", |
| "labels.json" |
| ], |
| "older": [ |
| "model.onnx", |
| "model.onnx.data", |
| "tokenizer.json", |
| "labels.json" |
| ], |
| "update_about": "A smaller version: 0.6 GB instead of 2.2 GB, a third faster, and the same punctuation on 99 words in 100. The old one is removed once it is in.", |
| "source": { |
| "repo": "kenrunio/transcriber-punctuation-onnx" |
| }, |
| "sha256": { |
| "model_int8.onnx": "016c7f8ed917f564ca16792d838c9f7a1d91f4b567a29569108a862d2da65fb0", |
| "tokenizer.json": "8124d1990cd91a86da7d51b0bd10b7913377f48710901e17b7db7b6f8cd5aee6", |
| "labels.json": "a19c8dc4400604b04a4da3cc356d7c5709110a0ce6770bd0c067697db88fd5a7" |
| } |
| }, |
| { |
| "id": "sounds", |
| "kind": "sounds", |
| "name": "Sound recognition (Audio Spectrogram Transformer, ONNX)", |
| "about": "For clean-up: tells coughs, throat clearing and sneezes from speech and other sounds. Optional.", |
| "languages": "Any", |
| "license": "BSD-3-Clause", |
| "size_mb": 91, |
| "files": [ |
| "onnx/model_int8.onnx", |
| "config.json" |
| ], |
| "source": { |
| "repo": "onnx-community/ast-finetuned-audioset-10-10-0.4593-ONNX", |
| "revision": "2fe67046c486b8b8bc90a7b469239b2dec822f72" |
| }, |
| "sha256": { |
| "onnx/model_int8.onnx": "6739e480a4faf4651f60d2238b0eb8cd58bead2a07ae1da5e2fbc72e3f7c98a6", |
| "config.json": "d4d347e95b00f4b1a0ea7eaf32bbbb2c246539ce1e64da89ffc0700c4a61ac8a" |
| } |
| }, |
| { |
| "id": "align", |
| "kind": "align", |
| "name": "Word timing (wav2vec2 base, ONNX)", |
| "about": "For clean-up: finds exactly where each word is, so ums are cut without touching the words beside them. Optional.", |
| "languages": "English", |
| "license": "Apache-2.0", |
| "size_mb": 378, |
| "files": [ |
| "onnx/model.onnx", |
| "vocab.json", |
| "config.json" |
| ], |
| "source": { |
| "repo": "onnx-community/wav2vec2-base-960h-ONNX", |
| "revision": "729c1a6730fb549c20a1c73a3d3f96f11020225e" |
| }, |
| "sha256": { |
| "onnx/model.onnx": "00b7cc69516c1ab63c429e63a2b543e4d42bb77441ec5b98ee935de175b00de1", |
| "vocab.json": "4178db26b3c7570f6a47f14ac6a1c7b32950b8c2800fb097287e53776934f1c5", |
| "config.json": "15c7cf6378153bdcb33fce27780ab9aae37fd154fbb674cacc3347992055d323" |
| } |
| } |
| ] |
| } |
|
|
