Instructions to use ninja/assis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/assis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ninja/assis")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ninja/assis") model = AutoModelForCTC.from_pretrained("ninja/assis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 475b5e33b06eb6dac675048148cddc6d0716c0c9a2635447498574d512bda524
- Size of remote file:
- 3.52 kB
- SHA256:
- 4eece180b0cc5a40f4cef2014e0950d2b86f057dc406b226ac5049d86b2b371f
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