Instructions to use Yulle/WhisperCheckpoints3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yulle/WhisperCheckpoints3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yulle/WhisperCheckpoints3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yulle/WhisperCheckpoints3") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yulle/WhisperCheckpoints3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yulle/WhisperCheckpoints3: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/Yulle/WhisperCheckpoints3/resolve/main/training_args.bin
- Command line
-
hf download hf://Yulle/WhisperCheckpoints3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yulle/WhisperCheckpoints3/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- eed258d895929a96adaea20f8e26b75c62f7ca493719f1c9b712091d8049871c
- Size of remote file:
- 4.86 kB
- SHA256:
- 662f797f8edcbb70becb0da2c572ae084cf28033a6f38f81db30986ba8ffae41
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