Instructions to use GENG/hubert_ls_2500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/hubert_ls_2500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/hubert_ls_2500")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/hubert_ls_2500") model = AutoModelForCTC.from_pretrained("GENG/hubert_ls_2500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scaler.pt from GENG/hubert_ls_2500: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/GENG/hubert_ls_2500/resolve/main/scaler.pt
- Command line
-
hf download hf://GENG/hubert_ls_2500/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/GENG/hubert_ls_2500/resolve/main/scaler.pt
559 Bytes
- Xet hash:
- 65388c930fcde07ba94d75fffe292959e8f1a4a1911851a28f5ad199939ad2c1
- Size of remote file:
- 559 Bytes
- SHA256:
- fd7f4ef7f801cc6f9dc90f4621568ea7d9cd7d0e629608613855f02aef394b93
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