Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sandiago21/whisper-large-v2-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandiago21/whisper-large-v2-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sandiago21/whisper-large-v2-german")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sandiago21/whisper-large-v2-german") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sandiago21/whisper-large-v2-german") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2dcfff21e5655cf804ecb4be619011037f08dc8ce145c38e888b69327803118a
- Size of remote file:
- 4.09 kB
- SHA256:
- c94bebd1f98bad042ee01cf14f7c21a3cf8bf72d07a0547e28851d0d8ad8d721
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