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:
- 8f34b11a9d9170d3c6eb3b67311fb9c1666e30815e28cfef72bb514e0bf425ae
- Size of remote file:
- 290 MB
- SHA256:
- bbbd110a07f9e0b2135ac77154f1d29ed37722a5d1067b77f54a39a7f6902002
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