Instructions to use sitwala/multilingual-whisper-v3-scripted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sitwala/multilingual-whisper-v3-scripted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sitwala/multilingual-whisper-v3-scripted")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sitwala/multilingual-whisper-v3-scripted") model = AutoModelForSpeechSeq2Seq.from_pretrained("sitwala/multilingual-whisper-v3-scripted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5541c91590df7160dc4e138de793f310c55e25d592a523f32402cda68140dfc
- Size of remote file:
- 5.62 kB
- SHA256:
- 50bb7cfbe94927ef53ec779d1401ef35f3794071c0d9b84f370d64b6823ee2ff
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