Instructions to use teoha/whisper-small-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use teoha/whisper-small-ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="teoha/whisper-small-ja")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("teoha/whisper-small-ja") model = AutoModelForSpeechSeq2Seq.from_pretrained("teoha/whisper-small-ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from teoha/whisper-small-ja: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/teoha/whisper-small-ja/resolve/main/training_args.bin
- Command line
-
hf download hf://teoha/whisper-small-ja/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/teoha/whisper-small-ja/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 01b5a1297eecbbe08fcf2bd64e3c181b547eee3609a799ac2559ea7fb448bb73
- Size of remote file:
- 4.09 kB
- SHA256:
- 4a6d430bc6a1d1c9989ae9fe406ef04c9dbb5d5521c13dcc866d5e358a9e3b5b
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