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 training_args.bin from GENG/hubert_5000_checkpoint_ls: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/GENG/hubert_5000_checkpoint_ls/resolve/main/training_args.bin
- Command line
-
hf download hf://GENG/hubert_5000_checkpoint_ls/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GENG/hubert_5000_checkpoint_ls/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 0350e09b66e8c006bc79c5b360acf0fd7aacc1cc046c2c463970af7ada67221f
- Size of remote file:
- 3.06 kB
- SHA256:
- 3419ede82fc2916f835ca06fb07cdbe2784f67223bd9a930645066e3badc8d64
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