Instructions to use Yulle/WhisperImprovementTest2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yulle/WhisperImprovementTest2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yulle/WhisperImprovementTest2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yulle/WhisperImprovementTest2") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yulle/WhisperImprovementTest2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yulle/WhisperImprovementTest2: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Yulle/WhisperImprovementTest2/resolve/main/training_args.bin
- Command line
-
hf download hf://Yulle/WhisperImprovementTest2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yulle/WhisperImprovementTest2/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 4ddfa8029cd97032eb30b96f7e755af8a6e3c2db59a81c423a1a48bc8afe94f9
- Size of remote file:
- 4.92 kB
- SHA256:
- 264c07106dba50f804d05d4b2da07e9ae45c4b281c16c54cc5fcff7ec0482002
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