Instructions to use ROGRANMAR/PRUEBA5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ROGRANMAR/PRUEBA5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ROGRANMAR/PRUEBA5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ROGRANMAR/PRUEBA5") model = AutoModelForCTC.from_pretrained("ROGRANMAR/PRUEBA5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ROGRANMAR/PRUEBA5: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/ROGRANMAR/PRUEBA5/resolve/main/training_args.bin
- Command line
-
hf download hf://ROGRANMAR/PRUEBA5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ROGRANMAR/PRUEBA5/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 78094e8d0a0796231aa155d84561bd3854095eae887e5a1e3c486e2bb9b3f2c1
- Size of remote file:
- 3.58 kB
- SHA256:
- b5c7e0614a51da2640825a5fca218a974e746a55666756f5db363cb9f10dd710
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