Instructions to use Sjdan/mst_hp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/mst_hp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/mst_hp2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/mst_hp2") model = AutoModelForCTC.from_pretrained("Sjdan/mst_hp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/mst_hp2: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/mst_hp2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/mst_hp2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/mst_hp2/resolve/main/training_args.bin
3 kB
- Xet hash:
- d3edb7718ff7d4d34c2baf250a438e9e339f9b9d484311b2358dc99313c5dc78
- Size of remote file:
- 3 kB
- SHA256:
- 2fbd1d7f24dafae4b723730e63606e2d99146e478c56cdf2bf3aff5332d0cb1e
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