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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70a0f97da41adca31769d61b7cec0b2ff15589f6013e8cf6d92c9497dce69553
- Size of remote file:
- 379 MB
- SHA256:
- 6b42c8453b96b203198c1c280a8821158ea3fa8dbbc2a6220cad1c1489c3e65e
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