Instructions to use NS-Y/whisper-tiny-he-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NS-Y/whisper-tiny-he-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NS-Y/whisper-tiny-he-6")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NS-Y/whisper-tiny-he-6") model = AutoModelForSpeechSeq2Seq.from_pretrained("NS-Y/whisper-tiny-he-6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b877e54e4f7517910fc88a5dc5cd5a88c657938c7659cfb6d438076f36e4a59
- Size of remote file:
- 3.77 kB
- SHA256:
- e66d586fca9adeb1a4e613be411e8319f20adead7959c4e59a2108ded7ce170b
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