Instructions to use devkyle/whisper-small-dp-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/whisper-small-dp-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/whisper-small-dp-v4")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/whisper-small-dp-v4") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/whisper-small-dp-v4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c26c2b50d1c558474332d54c5772bed29b29f42265aa57f76d77ff083add9913
- Size of remote file:
- 5.5 kB
- SHA256:
- 1a64446b4afdfdd55005c29d1af7d0e49d7ce453f951f62cf3bfa0f118c0c23e
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