Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
whisper
ASR
Speech Recognition
Hindi
Instructions to use mukish45/whisper-base-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukish45/whisper-base-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mukish45/whisper-base-hi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mukish45/whisper-base-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("mukish45/whisper-base-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccb87a0b2c0e634fcff5212a4d5648441607718fb7daf1eb69bb1f8b9fd75852
- Size of remote file:
- 290 MB
- SHA256:
- 2d278b312831cf812f8dfeb76fa86b54afae69524f72973cb5e2a61f3eb6eb41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.