Instructions to use nrshoudi/hubert_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrshoudi/hubert_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nrshoudi/hubert_new")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nrshoudi/hubert_new") model = AutoModelForCTC.from_pretrained("nrshoudi/hubert_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nrshoudi/hubert_new: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/nrshoudi/hubert_new/resolve/main/training_args.bin
- Command line
-
hf download hf://nrshoudi/hubert_new/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nrshoudi/hubert_new/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 47d4e0c9503f474e8a83725f3aaff443576475af9b0506342c0c17e073da5518
- Size of remote file:
- 5.11 kB
- SHA256:
- 37338c95b635fe7483ab7758b787343a0a702948e67e227a3f7b4beaf7008d90
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