Create README.md
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README.md
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---
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language:
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- de
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- en
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license: mit
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library_name: ctranslate2
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pipeline_tag: automatic-speech-recognition
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tags:
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- whisper-large-v3
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- ctranslate2
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- int8_float16
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- austrian-german
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- speech-to-text
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- localai
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- faster-whisper
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model_type: whisper
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base_model: openai/whisper-large-v3
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quantization: int8_float16
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inference: true
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datasets:
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- common_voice_15_0
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- mozilla-foundation/common_voice_16_1
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- own/callcenter_at
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metrics:
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- wer
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---
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# Whisper‐large-v3-DE-AT (CT2 INT8 + FP16)
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Feingetuntes Whisper-large-v3-Modell auf österreichisch-deutschen Sprachdaten.
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Diese Variante ist **komplett in [CTranslate2]-Format** vorliegend und wurde mit
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`--quantization int8_float16` exportiert.
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Dadurch halbiert sich der GPU-VRAM-Bedarf bei praktisch identischer Genauigkeit.
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| Eigenschaft | Wert |
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|------------------------|--------------------------------------------------|
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| Basismodell | `openai/whisper-large-v3` |
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| Quantisierung | **INT8-Gewichte** + FP16-Aktivierungen |
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| Größe (model.bin) | ≈ 5.6 GB |
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| Empfohlene Hardware | ≥ 16 GB GPU (VRAM) oder starke CPU mit AVX2/AVX-512 |
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| Compute Type YAML | `compute_type: int8_float16` |
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| Licence | MIT (wie Original) |
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---
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## 🛠️ Verwendung
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### LocalAI ≥ v3.0
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```yaml
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# whisper-large-v3-de-at.yaml
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name: whisper-large-v3-de-at
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backend: fast-whisper
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parameters:
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model: whisper-large-v3-de-at-ct2
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language: de
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translate: false
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compute_type: int8_float16
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vad_filter: true
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