Instructions to use Sjdan/CA_1_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/CA_1_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/CA_1_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/CA_1_2") model = AutoModelForCTC.from_pretrained("Sjdan/CA_1_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/CA_1_2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/CA_1_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/CA_1_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/CA_1_2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 053a4c86fbec9334d5253cc4ae0cd26acf9444e6ce0e4b5faf8ae8fb2bfdd10b
- Size of remote file:
- 3.45 kB
- SHA256:
- 4340b1ab45c87eba06f41400d2582e2dff76ca3f4bdc155794a900a97c1fba64
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