Automatic Speech Recognition
Transformers
PyTorch
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use wetq423fqsdv/repo_name with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wetq423fqsdv/repo_name with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="wetq423fqsdv/repo_name")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("wetq423fqsdv/repo_name") model = AutoModelForSpeechSeq2Seq.from_pretrained("wetq423fqsdv/repo_name", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6fd0857465181504fca41310c477cb49b49bea7039a2740d930b36448781302
- Size of remote file:
- 290 MB
- SHA256:
- 91cab53a4c6a45864e6baaea514f8874df71f64c5d105fc5f072739ffa5d9c4d
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