Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
German
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use basha3la2/whisper-base-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basha3la2/whisper-base-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basha3la2/whisper-base-de")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basha3la2/whisper-base-de") model = AutoModelForSpeechSeq2Seq.from_pretrained("basha3la2/whisper-base-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65eaf45caf3ebdee9a9bc82686e4499d0c46e0c1d5d35aa80ce8ab73e8657c35
- Size of remote file:
- 5.39 kB
- SHA256:
- 4562570329e0bac1201f754205d9dd81a118586ae2c4305a48462fe9a1f8b4d3
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