Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use SubsWay/my_whisper_test_check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SubsWay/my_whisper_test_check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SubsWay/my_whisper_test_check")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SubsWay/my_whisper_test_check") model = AutoModelForSpeechSeq2Seq.from_pretrained("SubsWay/my_whisper_test_check", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SubsWay/my_whisper_test_check: direct link, hf CLI and curl.
- Browser
- Download file 4.67 kB
-
https://huggingface.co/SubsWay/my_whisper_test_check/resolve/main/training_args.bin
- Command line
-
hf download hf://SubsWay/my_whisper_test_check/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SubsWay/my_whisper_test_check/resolve/main/training_args.bin
4.67 kB
- Xet hash:
- d2e84b64476679bcd59e83bf45d48dce4c6e5fcbb8fb148e544441c81b8a5b18
- Size of remote file:
- 4.67 kB
- SHA256:
- ec38b52007b27b04b6893016294eedc3502c3fcdb8ef27e87c9b16981cca31c1
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