Instructions to use MariaK/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MariaK/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MariaK/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("MariaK/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("MariaK/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 421c1c079dd28d165d53156be8fc3bb77b4b8eb9bdeb265925efe7c4a5b69189
- Size of remote file:
- 4.09 kB
- SHA256:
- 3dd0065bd0186cc2d8e449baf7cc209e3b222e3b27f9f43f3053d2adef769ba2
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