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 scaler.pt from GENG/hubert_ls_4500: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/GENG/hubert_ls_4500/resolve/main/scaler.pt
- Command line
-
hf download hf://GENG/hubert_ls_4500/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/GENG/hubert_ls_4500/resolve/main/scaler.pt
559 Bytes
- Xet hash:
- bdb3bab6e216f4bd166c9c517f0816839ec5468f99a06340aa721f0e7f8dce57
- Size of remote file:
- 559 Bytes
- SHA256:
- bbe1d01e7eabf61ce9aaf7b85a2cbb5611e82862d626eb4f47431fa11c129a13
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