Instructions to use Almoooo/hasa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Almoooo/hasa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Almoooo/hasa")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Almoooo/hasa") model = AutoModelForSpeechSeq2Seq.from_pretrained("Almoooo/hasa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d7509f9d0e3c337b047b1d901dc8743c9527f440566de46adc7ca1c5641bd9c
- Size of remote file:
- 64.8 MB
- SHA256:
- 5a3b983d1f11ace408ea1ed1c7f74d301d6bc167d58ae8369e3f4b2e5291ee4b
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