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:
- 747edf3cbddfd59db6546ebecb5bae915b1251b4612d2f15979c928ead38810a
- Size of remote file:
- 967 MB
- SHA256:
- 22a194d21569af4d215383b5ce7ce4359c81bf7eb59b174a4b9adb8bc6c346ca
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