Instructions to use Sjdan/CA_SID_M11_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/CA_SID_M11_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/CA_SID_M11_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/CA_SID_M11_2") model = AutoModelForCTC.from_pretrained("Sjdan/CA_SID_M11_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/CA_SID_M11_2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/CA_SID_M11_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/CA_SID_M11_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/CA_SID_M11_2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 4096acf10db710bb404075ffbf8c29c06f1baf7b1bef03f3ec30a2a457e14796
- Size of remote file:
- 3.45 kB
- SHA256:
- 0a6b8b62e45d5590f08ba18cea4480c70da6044b84c52d99aa654e02bfbc8641
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