Instructions to use yash072/Whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yash072/Whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yash072/Whisper")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("yash072/Whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("yash072/Whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yash072/Whisper: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/yash072/Whisper/resolve/main/training_args.bin
- Command line
-
hf download hf://yash072/Whisper/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yash072/Whisper/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- f8da102955b6f4e446c64ebc3af195ae8af8fff6673f9dc132006d4e650ae14c
- Size of remote file:
- 5.56 kB
- SHA256:
- b2cacdb271797aa2baaf825477c659d63e4eada7fa0b59f8e09418639e8f8f19
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