Instructions to use alphaedge-ai/whisper-medium-sna-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/whisper-medium-sna-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="alphaedge-ai/whisper-medium-sna-32768")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("alphaedge-ai/whisper-medium-sna-32768") model = AutoModelForSpeechSeq2Seq.from_pretrained("alphaedge-ai/whisper-medium-sna-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 420eae4ea4dcdca103fa855b04d4bd41532e6f6c278f80d4631a2058956f09fc
- Size of remote file:
- 1.49 GB
- SHA256:
- 2d9e167fd44db8ec3647877540f25486cb05cdc62e4663661e31860e72bd4ac4
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