Instructions to use Sjdan/torgo_c_a_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/torgo_c_a_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/torgo_c_a_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/torgo_c_a_2") model = AutoModelForCTC.from_pretrained("Sjdan/torgo_c_a_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/torgo_c_a_2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Sjdan/torgo_c_a_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/torgo_c_a_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/torgo_c_a_2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- f51cc45f967b7666c69695192b90c76ec5b58b808ec1492f2413524877fed818
- Size of remote file:
- 3.58 kB
- SHA256:
- 6e4ef1e76d462f9ec2f71159b989608dfcfa54b139ad281f59ac280b95ecc2aa
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