Instructions to use Yulle/WhisperImprovementTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yulle/WhisperImprovementTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yulle/WhisperImprovementTest")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yulle/WhisperImprovementTest") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yulle/WhisperImprovementTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yulle/WhisperImprovementTest: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/Yulle/WhisperImprovementTest/resolve/main/training_args.bin
- Command line
-
hf download hf://Yulle/WhisperImprovementTest/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yulle/WhisperImprovementTest/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- d5f03832eac2662307242d92366a18e4793d99804030a9590014dd6cd17984b4
- Size of remote file:
- 4.86 kB
- SHA256:
- 6d5f935a94f7487bbfd58af90f4abb7c9cf3c529f48e4bb351a23bd400dd0861
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