Instructions to use akahana/whisper-small-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akahana/whisper-small-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="akahana/whisper-small-id")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("akahana/whisper-small-id") model = AutoModelForSpeechSeq2Seq.from_pretrained("akahana/whisper-small-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d6a7131f6ddc1c8318a43e83c9b17fa0d415102464fec08329322164ccb53b1
- Size of remote file:
- 5.5 kB
- SHA256:
- fb135cf351ee4d05cdedd7f4f6903ad9cb04ec35b66fb1c614fde5a309950d32
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