Instructions to use Sjdan/f05_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/f05_main with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/f05_main")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/f05_main") model = AutoModelForCTC.from_pretrained("Sjdan/f05_main", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/f05_main: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/f05_main/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/f05_main/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/f05_main/resolve/main/training_args.bin
3 kB
- Xet hash:
- 9395c90dd212fe176e2cb212a7bdd45d8b38dc08ef46e6ce37eacced385ba9e7
- Size of remote file:
- 3 kB
- SHA256:
- 68d3593b18802f2719ec58878f67a7d47a6569661c81c54213ec871aa72ae301
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