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")# 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 pytorch_model.bin from speech31/hubert-base-english-ipa: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/speech31/hubert-base-english-ipa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://speech31/hubert-base-english-ipa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/speech31/hubert-base-english-ipa/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 68b2134c8884f1a4ad1b321495f4e7f5abf2db94821af1fad27009b31e5fdb57
- Size of remote file:
- 378 MB
- SHA256:
- e90a0cf2d07736816cf64424b0fbf982331caafacd6b7d853226434080b976ff
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