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") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- 2.24 kB
- 1.25 kB
- 32 Bytes
- 240 Bytes
- 2.16 kB
- 240 Bytes
- 665 kB
- 374 kB
- 9.77 kB
- 81 Bytes
- 2.37 MB
- 9.53 kB
- 9.57 kB
- 1.69 MB
- 1.52 MB
- 1.14 MB
- 2.12 MB
- 1.81 MB
- 574 kB
- 259 kB
- 4.91 kB
- 2.5 MB
- 1.1 MB
- 81 Bytes
- 8.32 kB
- 606 kB
- 890 kB
- 2.54 MB
- 231 kB
- 158 kB
- 98.6 kB
- 664 kB
- 2.04 MB
- 231 kB
- 15.4 kB
- 14.9 kB
- 3.76 MB
- 1.26 GB xet
- 31.3 MB xet
- 38 MB xet
- 36.9 MB xet
- 24.7 MB xet
- 2.61 MB
- 31 MB xet
- 1.09 MB
- 6.67 MB xet
- 2.49 MB
- 254 Bytes
- 96 Bytes
- 1.1 kB