Instructions to use Sjdan/f05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/f05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/f05")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/f05") model = AutoModelForCTC.from_pretrained("Sjdan/f05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/f05: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/f05/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Sjdan/f05@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/f05/resolve/refs%2Fpr%2F1/training_args.bin
3 kB
- Xet hash:
- 7501a6a49be79531685f49f3d2dbd9b34b8da83bba6e5f15f0f6b9a450b30e01
- Size of remote file:
- 3 kB
- SHA256:
- 04d06c843700ce9f9e998b3f3744b1ab1ecc881dc7b5558764da4c998087c1d1
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