Instructions to use Sjdan/mst_hp_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/mst_hp_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/mst_hp_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/mst_hp_1") model = AutoModelForCTC.from_pretrained("Sjdan/mst_hp_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/mst_hp_1: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/Sjdan/mst_hp_1/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/mst_hp_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/mst_hp_1/resolve/main/training_args.bin
3 kB
- Xet hash:
- fdc65f1d6573b9965a2c4393591a232e5218e9f888ed2f5fcb246395cb646ea2
- Size of remote file:
- 3 kB
- SHA256:
- 08e9c105828c90bf53bd4062286bff10537317c43048c3ae987efc2ab295d75a
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