Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
German
whisper
Eval Results (legacy)
Instructions to use sanchit-gandhi/distil-whisper-large-v3-de-kd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/distil-whisper-large-v3-de-kd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/distil-whisper-large-v3-de-kd")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sanchit-gandhi/distil-whisper-large-v3-de-kd") model = AutoModelForSpeechSeq2Seq.from_pretrained("sanchit-gandhi/distil-whisper-large-v3-de-kd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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README.md
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language:
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library_name: transformers
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---
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# Distil-Whisper large-v3 German
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language:
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- de
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library_name: transformers
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base_model: openai/whisper-large-v3
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model-index:
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- name: Distil-Whisper large-v3 De
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: Common Voice 15.0
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type: mozilla-foundation/common_voice_15_0
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args: 'Config: de'
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metrics:
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- type: wer
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value: 6.324
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name: Wer
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---
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# Distil-Whisper large-v3 German
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