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:
- f3a3449f27cf272b0f6c36f92be9e92b3b8d33a80d55523692dab6decb6ea8ef
- Size of remote file:
- 4.14 kB
- SHA256:
- 7b9b39ff64c77c29453efe75a4424ce31b4db769b0d82a46a86d492f7d823b9c
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