Instructions to use Sjdan/sw_hp4_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/sw_hp4_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/sw_hp4_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/sw_hp4_2") model = AutoModelForCTC.from_pretrained("Sjdan/sw_hp4_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sjdan/sw_hp4_2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Sjdan/sw_hp4_2/resolve/main/training_args.bin
- Command line
-
hf download hf://Sjdan/sw_hp4_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sjdan/sw_hp4_2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 310100356ff333c3ddaec604a4a61554d1f56feaf2f8889789efff429e4e6dab
- Size of remote file:
- 3.58 kB
- SHA256:
- 0f24620424901bedd9d82599550b8910580175216d80cbe4fa13d3fe9a1e47fc
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