Instructions to use Sjdan/hp_mst_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/hp_mst_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/hp_mst_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/hp_mst_1") model = AutoModelForCTC.from_pretrained("Sjdan/hp_mst_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/hp_mst_1: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/Sjdan/hp_mst_1/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/hp_mst_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/hp_mst_1/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 613d9be56000d233959282b22fe0cfb10c8514e5a1e82b8cadd6822783564387
- Size of remote file:
- 3.45 kB
- SHA256:
- d869601d8e5a0f7b5270f8b05fffbe01c23a18e29631a942b6630eb7830e5af2
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