Instructions to use Sjdan/mst_hp3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/mst_hp3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/mst_hp3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/mst_hp3") model = AutoModelForCTC.from_pretrained("Sjdan/mst_hp3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/mst_hp3: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/mst_hp3/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/mst_hp3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/mst_hp3/resolve/main/training_args.bin
3 kB
- Xet hash:
- ba03154249cf38e69464cd182a70ae4f85034c006776658a49ea3ba92a323ae4
- Size of remote file:
- 3 kB
- SHA256:
- d2ca698054594bcf91cbf73b7f0298cf7672d78fe991f7f93d04ceef2c712c81
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