Instructions to use Yulle/WhisperCheckpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yulle/WhisperCheckpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yulle/WhisperCheckpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yulle/WhisperCheckpoints") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yulle/WhisperCheckpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yulle/WhisperCheckpoints: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/Yulle/WhisperCheckpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://Yulle/WhisperCheckpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yulle/WhisperCheckpoints/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 8ff4b3b96fa3b8921e6d13d32906139d71eaae818b6ec2defdb9da7f42e4a896
- Size of remote file:
- 4.86 kB
- SHA256:
- bd96b54598c8d1869a42ab53f52530b799c4f9d48c084a8d1b3ccc52f01c33a4
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