Instructions to use Sjdan/C6_A_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/C6_A_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/C6_A_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/C6_A_2") model = AutoModelForCTC.from_pretrained("Sjdan/C6_A_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/C6_A_2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/C6_A_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/C6_A_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/C6_A_2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 4e759f3124d580baf53555c819cd761efe9bd26c56fb84b34d1111b63a5df143
- Size of remote file:
- 3.45 kB
- SHA256:
- 56ade02b6b07699861974ad6d9c57648165357999caa242cc1bd286e6bb84716
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