Automatic Speech Recognition
Transformers
Safetensors
PyTorch
German
Swiss German
whisper
speech-to-text
swiss-german
schweizerdeutsch
Eval Results (legacy)
Instructions to use Flurin17/whisper-large-v3-turbo-swiss-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Flurin17/whisper-large-v3-turbo-swiss-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Flurin17/whisper-large-v3-turbo-swiss-german")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Flurin17/whisper-large-v3-turbo-swiss-german") model = AutoModelForSpeechSeq2Seq.from_pretrained("Flurin17/whisper-large-v3-turbo-swiss-german", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15f319c8ceb1f55956f6df710bc7376bfcc25e639bb71141fe588a42e4cc2dcb
- Size of remote file:
- 6.23 kB
- SHA256:
- f9bbad6209d784849537b318fbd7654ebbee403d1d47a0061aadbe6750dc3bdf
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