Instructions to use DRAGOO/assis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DRAGOO/assis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DRAGOO/assis")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DRAGOO/assis") model = AutoModelForCTC.from_pretrained("DRAGOO/assis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98506d19a9c93dab1623485ee49a0c2d3867dad60e1d4c255db4404068cc602d
- Size of remote file:
- 378 MB
- SHA256:
- 1205595b663b2b6c983545b3d6cf7ace3bc1cea92444c828c7a93d593fc87ab2
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