Instructions to use Priyanship/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Priyanship/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Priyanship/output")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Priyanship/output") model = AutoModelForCTC.from_pretrained("Priyanship/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cba747eabea038185074b15a1ec99779b4a292c38d9f69eb870af96321b1577f
- Size of remote file:
- 5.5 kB
- SHA256:
- 071e6d4afa796c2acebfd47a3664f0a7ea8528a7313422e5fdfafeede8b71d61
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