Instructions to use dmmagdal/whisper-tiny-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmmagdal/whisper-tiny-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dmmagdal/whisper-tiny-onnx")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("dmmagdal/whisper-tiny-onnx") model = AutoModelForSpeechSeq2Seq.from_pretrained("dmmagdal/whisper-tiny-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc1089340f727fb6d72594bc6e2419ea9948adb78fc9c026887c1e8eba7c45a2
- Size of remote file:
- 198 MB
- SHA256:
- e08bebf8d6cb8c930714ec015a99ab689ccb0fda084ff0947a4800a492409b74
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