Instructions to use Sjdan/mst_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/mst_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/mst_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/mst_2") model = AutoModelForCTC.from_pretrained("Sjdan/mst_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/mst_2: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/mst_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/mst_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/mst_2/resolve/main/training_args.bin
3 kB
- Xet hash:
- 63d69c05d84c8cc8b084d63a05ca65da1245942a23ec32d312731a37108b39fd
- Size of remote file:
- 3 kB
- SHA256:
- 1258f53e31627b669e00ce2a1b27d28fbef839afddf80cab6e0a81ee3ab78a7d
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