Instructions to use darthPanda/whisper-small-ur1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darthPanda/whisper-small-ur1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="darthPanda/whisper-small-ur1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("darthPanda/whisper-small-ur1") model = AutoModelForSpeechSeq2Seq.from_pretrained("darthPanda/whisper-small-ur1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bc7d3af889f945ab60fa40d1c53d7bcd14eeb2fa6f0c2b2c92583cb335902a2
- Size of remote file:
- 967 MB
- SHA256:
- 26b2ea037ccf6082c4b674d35268c09fb63eacef9a68f6a0f27a2bd1bd86347f
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