Instructions to use Sjdan/switch_high_x_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/switch_high_x_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/switch_high_x_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/switch_high_x_2") model = AutoModelForCTC.from_pretrained("Sjdan/switch_high_x_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/switch_high_x_2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Sjdan/switch_high_x_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/switch_high_x_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/switch_high_x_2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- a3b64894f26e3ec1864ad4dcd3e44597b8fd47aa829b973c55b02d0b2663bf08
- Size of remote file:
- 3.58 kB
- SHA256:
- 79f2c2a98967176b942c396b95d3a9b05a3bef8f3afaced38782789befa939ad
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