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hubert
ryota-komatsu/hubert
hubert is a machine learning model from ryota-komatsu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
- Model type: Hubert-Base - Language(s) (NLP): English - License: MIT
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.safetensors428 MB · 100%
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Base models
Model card
From the Hugging Face model README
Hubert-Base
<!-- Provide a quick summary of what the model is/does. -->Model Details
Model Description
<!-- Provide a longer summary of what this model is. -->- Model type: Hubert-Base
- Language(s) (NLP): English
- License: MIT
How to Get Started with the Model
Use the code below to get started with the model.
sudo apt install git-lfs # for UTMOS
conda create -y -n py310 -c pytorch -c nvidia -c conda-forge python=3.10.18 pip=24.0 faiss-gpu=1.12.0
conda activate py310
pip install -r requirements/requirements.txt
sh scripts/setup.sh
import torchaudio
from src.s5hubert import S5HubertForSyllableDiscovery
wav_path = "/path/to/wav"
# download pretrained models from hugging face hub
encoder = S5HubertForSyllableDiscovery.from_pretrained("ryota-komatsu/hubert", device_map="cuda")
# load a waveform
waveform, sr = torchaudio.load(wav_path)
waveform = torchaudio.functional.resample(waveform, sr, 16000)
# encode a waveform into syllabic units
outputs = encoder(waveform.to(encoder.device))
units = outputs[0]["units"] # [3950, 67, ..., 503]
- Library
- transformers
- Type
- hubert
- License
- mit
- Languages
- en
- Created
- Jan 22, 2026
- Updated
- Jan 23, 2026