Instructions to use alphaedge-ai/whisper-medium-hrv-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/whisper-medium-hrv-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-hrv-32768")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("alphaedge-ai/whisper-medium-hrv-32768") model = AutoModelForSpeechSeq2Seq.from_pretrained("alphaedge-ai/whisper-medium-hrv-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ac66d8a8f85c79bdf5d29ee90be19cbbff6a1d63f53129ceca80115406a1840
- Size of remote file:
- 1.49 GB
- SHA256:
- 4d399cf2720f3dcd4c3a48428ad42a2c1bdae68effd6594d5ba5d923a3b2b419
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