Instructions to use moonseok/result_Ver3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonseok/result_Ver3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="moonseok/result_Ver3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("moonseok/result_Ver3") model = AutoModelForCTC.from_pretrained("moonseok/result_Ver3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from moonseok/result_Ver3: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/moonseok/result_Ver3/resolve/main/training_args.bin
- Command line
-
hf download hf://moonseok/result_Ver3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/moonseok/result_Ver3/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 4111ee63ed3e31d79a07efea040566c8c8766242b1b1bfd12769889253f8ab88
- Size of remote file:
- 4.54 kB
- SHA256:
- 4f34a593e9c8673b893569603359e677f2e1013351485989a12f01fd17213e91
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