Instructions to use CianKim/whisper-medium-kor_eng_medium_ed_ev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CianKim/whisper-medium-kor_eng_medium_ed_ev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CianKim/whisper-medium-kor_eng_medium_ed_ev")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CianKim/whisper-medium-kor_eng_medium_ed_ev") model = AutoModelForSpeechSeq2Seq.from_pretrained("CianKim/whisper-medium-kor_eng_medium_ed_ev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CianKim/whisper-medium-kor_eng_medium_ed_ev: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/CianKim/whisper-medium-kor_eng_medium_ed_ev/resolve/main/training_args.bin
- Command line
-
hf download hf://CianKim/whisper-medium-kor_eng_medium_ed_ev/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CianKim/whisper-medium-kor_eng_medium_ed_ev/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 087b1e4c587e2f37060fd3eb1a17d55992b738e9e069709b40ad69a91508ce20
- Size of remote file:
- 5.5 kB
- SHA256:
- 97f002abc62ffce68adc21442b497ff4a8fa111a7563a43d4c4017e9da37286a
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