Instructions to use yongchanskii/Whisper-for-developers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yongchanskii/Whisper-for-developers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yongchanskii/Whisper-for-developers")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("yongchanskii/Whisper-for-developers") model = AutoModelForSpeechSeq2Seq.from_pretrained("yongchanskii/Whisper-for-developers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c8b0314c11955b70c7337755ca186ce62f46562cdbcae43787c085ec32b3567
- Size of remote file:
- 3.09 GB
- SHA256:
- b08bcaf68e40592fb7e08103a7b5c3a00bf292db6d6ac67f06285a1a4f38c1cc
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