Automatic Speech Recognition
Transformers
PyTorch
German
whisper
sbb-asr
Generated from Trainer
Eval Results (legacy)
Instructions to use marccgrau/whisper-small-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marccgrau/whisper-small-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marccgrau/whisper-small-best")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("marccgrau/whisper-small-best") model = AutoModelForSpeechSeq2Seq.from_pretrained("marccgrau/whisper-small-best") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2148b6a47cc4b8e592a37356c3da880cbd787282dfc61e7832448c40a8f3fccd
- Size of remote file:
- 3.52 kB
- SHA256:
- 91fb2e75f03b18ad78957207b0efed88a9181bf811b4f3eb794fb7253cbfd8db
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