Instructions to use GENG/hubert_ls_4500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/hubert_ls_4500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/hubert_ls_4500")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/hubert_ls_4500") model = AutoModelForCTC.from_pretrained("GENG/hubert_ls_4500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from GENG/hubert_ls_4500: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/GENG/hubert_ls_4500/resolve/main/training_args.bin
- Command line
-
hf download hf://GENG/hubert_ls_4500/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GENG/hubert_ls_4500/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- 591f0214569279bec345c67191c1e7fca06c6e550586c8b5230079646efc3412
- Size of remote file:
- 3.12 kB
- SHA256:
- 97b3795c614246ed0e3e462c09a707461cfc61ed99ffbcafe5992312af536449
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