Instructions to use nnaik39/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nnaik39/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nnaik39/content")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nnaik39/content") model = AutoModelForCTC.from_pretrained("nnaik39/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a67e57cc72017cf9fcdd11446b8e05354d520ae38580b8328c59d7de18c7065f
- Size of remote file:
- 5.05 kB
- SHA256:
- 35c34ae55e12a8c06eb7ba1be20d1b17bc07cb411adc102de01c3ff1f671366d
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