Instructions to use speech31/hubert-base-english-ipa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use speech31/hubert-base-english-ipa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="speech31/hubert-base-english-ipa")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("speech31/hubert-base-english-ipa") model = AutoModelForCTC.from_pretrained("speech31/hubert-base-english-ipa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from speech31/hubert-base-english-ipa: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/speech31/hubert-base-english-ipa/resolve/main/training_args.bin
- Command line
-
hf download hf://speech31/hubert-base-english-ipa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/speech31/hubert-base-english-ipa/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 3efe9613427589fa8f0abe0353cb3d753372f5cd216617c3648dcbe72472cf21
- Size of remote file:
- 2.86 kB
- SHA256:
- 51cde43985a0b309ff16c2f2c073f43e57ffce5c1e19efd52038a40ce294424f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.