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 optimizer.pt from GENG/hubert_ls_4500: direct link, hf CLI and curl.
- Browser
- Download file 722 MB
-
https://huggingface.co/GENG/hubert_ls_4500/resolve/main/optimizer.pt
- Command line
-
hf download hf://GENG/hubert_ls_4500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/GENG/hubert_ls_4500/resolve/main/optimizer.pt
722 MB
- Xet hash:
- c35d99563842817abf265edf302392bfebc763b47f88639f75ebe96034f8237a
- Size of remote file:
- 722 MB
- SHA256:
- 39d66044d4cd1ad6322223735fa244dbe31ff952df92fcf4cb7126e537aa2b47
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