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:
- a012831d038adc6b334e80e2bb0b734e78f2a915bf08a76b65a027eaf0f9c1a7
- Size of remote file:
- 6.17 GB
- SHA256:
- b5a01b75644ec215e199f168d5c81993a7c9c9d2433f7fd537ef053e176b393f
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