Instructions to use parthiv11/indic_whisper_hi_multi_gpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parthiv11/indic_whisper_hi_multi_gpu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="parthiv11/indic_whisper_hi_multi_gpu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("parthiv11/indic_whisper_hi_multi_gpu") model = AutoModelForSpeechSeq2Seq.from_pretrained("parthiv11/indic_whisper_hi_multi_gpu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 823214b23ffe71909cfb88e7ad5ee8841351b79316b9188acee2611900dd4235
- Size of remote file:
- 1.53 GB
- SHA256:
- 858e7f4a713da38a5b5f2cd5bd01506db3e49bb156653de3bb74bd4605be25e8
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