Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use gingercake01/STT_15000_4method_audio_basev1_0607 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gingercake01/STT_15000_4method_audio_basev1_0607 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="gingercake01/STT_15000_4method_audio_basev1_0607")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("gingercake01/STT_15000_4method_audio_basev1_0607") model = AutoModelForSpeechSeq2Seq.from_pretrained("gingercake01/STT_15000_4method_audio_basev1_0607") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c2f5bc8680dd9a0a8df9c8c349225aaf9d39aa6d2911fc89bbe392c205ff945
- Size of remote file:
- 290 MB
- SHA256:
- 0ef9fc3bdaba68ac36488771b2400931f47912b8516c0607da767e73ec9c402b
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