Instructions to use GENG/hubert_5000_checkpoint_ls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GENG/hubert_5000_checkpoint_ls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GENG/hubert_5000_checkpoint_ls")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GENG/hubert_5000_checkpoint_ls") model = AutoModelForCTC.from_pretrained("GENG/hubert_5000_checkpoint_ls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from GENG/hubert_5000_checkpoint_ls: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/GENG/hubert_5000_checkpoint_ls/resolve/main/scheduler.pt
- Command line
-
hf download hf://GENG/hubert_5000_checkpoint_ls/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/GENG/hubert_5000_checkpoint_ls/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- 6843a88e63d2521f35149b35d3348d325759b9cbca8f5fc3c360f53631ba697e
- Size of remote file:
- 623 Bytes
- SHA256:
- ad05380f36fcdad7d0489004cb970c3403e0c6f4d64ccddede393f8ca4940101
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