Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
Korean
hubert
feature-extraction
speech
audio
custom_code
Instructions to use team-lucid/hubert-large-korean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/hubert-large-korean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="team-lucid/hubert-large-korean", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("team-lucid/hubert-large-korean", trust_remote_code=True) model = AutoModel.from_pretrained("team-lucid/hubert-large-korean", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b28bb5632179eecf02eb342d1666f065ac4181e3a417a6c13e3f05ae615018cf
- Size of remote file:
- 1.26 GB
- SHA256:
- 4d4e116a4e1eb9f9615f2099544736b5b2d5730f08f9d75bdc04fd7a90996f8b
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