Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Dutch
whisper
whisper-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use GeoffVdr/whisper-medium-nlcv11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeoffVdr/whisper-medium-nlcv11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GeoffVdr/whisper-medium-nlcv11")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GeoffVdr/whisper-medium-nlcv11") model = AutoModelForSpeechSeq2Seq.from_pretrained("GeoffVdr/whisper-medium-nlcv11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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model-index:
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co2_eq_emissions:
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emissions: 2930
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source: https://mlco2.github.io/impact/
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- nl
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license: apache-2.0
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tags:
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- whisper-event
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- hf-asr-leaderboard
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Medium nl - GeoffVdr
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: mozilla-foundation/common_voice_11_0
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type: mozilla-foundation/common_voice_11_0
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config: nl
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split: test
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args: nl
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metrics:
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- name: Wer
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type: wer
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value: 7.514
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co2_eq_emissions:
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emissions: 2930
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source: https://mlco2.github.io/impact/
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