Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use oceanstar/bridze with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oceanstar/bridze with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oceanstar/bridze")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("oceanstar/bridze") model = AutoModelForSpeechSeq2Seq.from_pretrained("oceanstar/bridze") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01e26484e45590a64da81332c817096d0a73c4bfd2c0d6bbd815cfbcd3dc72d5
- Size of remote file:
- 290 MB
- SHA256:
- ad17bc4fae60d028fa0d170865dec59872ef78845fc879813c3a1f03f6bde775
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