Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
Korean
hubert
feature-extraction
speech
audio
custom_code
Instructions to use team-lucid/hubert-base-korean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/hubert-base-korean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="team-lucid/hubert-base-korean", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("team-lucid/hubert-base-korean", trust_remote_code=True) model = AutoModel.from_pretrained("team-lucid/hubert-base-korean", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb14879e0fc945cb8a1d52b65ff9289300a219d5b033968cda963bd4bb43087c
- Size of remote file:
- 378 MB
- SHA256:
- 931f6232879f8eadf7dbd9e00e1fa4cac61ad269af89d509b2ed75009b1a02c5
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