Instructions to use Sjdan/CA_SID_F03_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/CA_SID_F03_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/CA_SID_F03_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/CA_SID_F03_2") model = AutoModelForCTC.from_pretrained("Sjdan/CA_SID_F03_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/CA_SID_F03_2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/CA_SID_F03_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/CA_SID_F03_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/CA_SID_F03_2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 736b95372537c1129c9129fbd04c2130a1688536f4b95dd3eb040fd267e45895
- Size of remote file:
- 3.45 kB
- SHA256:
- b1fbc60a042836ef7e8d3d55b7814695a4eb8c02b05419a904660d73ab7d957e
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