Instructions to use aware-ai/whisper-tiny-european with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aware-ai/whisper-tiny-european with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aware-ai/whisper-tiny-european")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("aware-ai/whisper-tiny-european") model = AutoModelForSpeechSeq2Seq.from_pretrained("aware-ai/whisper-tiny-european") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfa84c883c9acf0228a4fbe1afc236bce7e94e8c09e9bca71f8fcbb7cd2ee93a
- Size of remote file:
- 151 MB
- SHA256:
- 12a939238b7b02ed9e3edd32ddcce163f241ca0ec9f0dd7be0e2fccfc0655186
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.