Instructions to use Sjdan/switch_verylow_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/switch_verylow_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/switch_verylow_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/switch_verylow_2") model = AutoModelForCTC.from_pretrained("Sjdan/switch_verylow_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/switch_verylow_2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Sjdan/switch_verylow_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/switch_verylow_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/switch_verylow_2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- dfcd8a4c581acc1bcd049ffda03f8b519f2684a33582ba94962107c8a7f47eaf
- Size of remote file:
- 3.58 kB
- SHA256:
- 2151e08cc6384a70b5c6e95fc03079dd10e1b9d52213f1a0e7d3099ecad9c34a
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