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:
- c0cbca504c31f762ce6583a7e9b7d0e270681ea5dbc4f6ca812b06596999fa24
- Size of remote file:
- 151 MB
- SHA256:
- 1422666e0f086325974a74dbe91228a5dcee17e5d3d420387d626a193285c945
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