Instructions to use primeline/whisper-tiny-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use primeline/whisper-tiny-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="primeline/whisper-tiny-german")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("primeline/whisper-tiny-german") model = AutoModelForSpeechSeq2Seq.from_pretrained("primeline/whisper-tiny-german") - Notebooks
- Google Colab
- Kaggle
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README.md
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| Model | Parameters | link |
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| Whisper large v3 german | 1.54B | [link](https://huggingface.co/primeline/whisper-large-v3-german) |
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| Distil-whisper large v3 german | 756M | [link](https://huggingface.co/primeline/whisper-large-v3-german) |
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| tiny whisper | 37.8M | [link](https://huggingface.co/primeline/whisper-tiny-german) |
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### Training hyperparameters
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| Model | Parameters | link |
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| Whisper large v3 german | 1.54B | [link](https://huggingface.co/primeline/whisper-large-v3-german) |
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| Distil-whisper large v3 german | 756M | [link](https://huggingface.co/primeline/distil-whisper-large-v3-german) |
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| tiny whisper | 37.8M | [link](https://huggingface.co/primeline/whisper-tiny-german) |
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### Training hyperparameters
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