Instructions to use 42MARU/ko-spelling-wav2vec2-conformer-del-1s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 42MARU/ko-spelling-wav2vec2-conformer-del-1s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="42MARU/ko-spelling-wav2vec2-conformer-del-1s")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("42MARU/ko-spelling-wav2vec2-conformer-del-1s") model = AutoModelForCTC.from_pretrained("42MARU/ko-spelling-wav2vec2-conformer-del-1s") - Notebooks
- Google Colab
- Kaggle
from scratch로 pre_trained된 모델
#2
by ppakji - opened
안녕하세요. 내용 잘 보았습니다.
Readme 내용 중 '해당 모델은 wav2vec2-conformer base architecture에 scratch pre-training 되었습니다.'라고 기재해놓으셨는데,
혹시 해당 pre-trained model도 업로드 해주실 수 있으신가요?
답변 감사합니다!