Instructions to use Apness/rururu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apness/rururu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Apness/rururu")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Apness/rururu") model = AutoModelForSpeechSeq2Seq.from_pretrained("Apness/rururu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d19abaf5166b19e366383702120b801cd4981e70ba9e474ed1a077fd413ea7f
- Size of remote file:
- 4.73 kB
- SHA256:
- 6313eed0d7d7860493618684504f2f2ab7f82a31dddbd35eaa6e828668d52b97
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