Instructions to use veghar/whisper-small-hindi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use veghar/whisper-small-hindi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="veghar/whisper-small-hindi")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("veghar/whisper-small-hindi") model = AutoModelForSpeechSeq2Seq.from_pretrained("veghar/whisper-small-hindi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from veghar/whisper-small-hindi: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/veghar/whisper-small-hindi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://veghar/whisper-small-hindi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/veghar/whisper-small-hindi/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- d7e5b3240507146f8f5fb214d7555d7922c38868e1a38cf88d27d0a0139de429
- Size of remote file:
- 967 MB
- SHA256:
- b24c9ccd8f2300bc23830dcb5fc67a010dfccf7690fe6bd321e1b684aaff7a7e
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