Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
korean
call-audio
Generated from Trainer
Eval Results (legacy)
Instructions to use Cathle/repo_name with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cathle/repo_name with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cathle/repo_name")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Cathle/repo_name") model = AutoModelForSpeechSeq2Seq.from_pretrained("Cathle/repo_name") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40043c89a4cd497d6af449cb7b6644b7c1d98a3fbbc33949ad0e7a82b803899c
- Size of remote file:
- 5.43 kB
- SHA256:
- 46372a963c7ca4b96a2c5cf3c641ebd8309c12fb406e6660c3fa9aa8b32155fe
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