Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use freshpearYoon/largev2_temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use freshpearYoon/largev2_temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="freshpearYoon/largev2_temp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("freshpearYoon/largev2_temp") model = AutoModelForSpeechSeq2Seq.from_pretrained("freshpearYoon/largev2_temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1af1a3b8a4a7f0a03aea264309f04098f65d099ea9375b129c9382e6039243cd
- Size of remote file:
- 4.48 kB
- SHA256:
- 6f374029da671d6f38e493b18f0f55068cce900e3c3823ea08add87344fb0dca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.