Instructions to use drepic/whisper-small-jp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drepic/whisper-small-jp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="drepic/whisper-small-jp")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("drepic/whisper-small-jp") model = AutoModelForSpeechSeq2Seq.from_pretrained("drepic/whisper-small-jp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ct2/tokenizer.json from drepic/whisper-small-jp: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
-
https://huggingface.co/drepic/whisper-small-jp/resolve/main/ct2/tokenizer.json
- Command line
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hf download hf://drepic/whisper-small-jp/ct2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/drepic/whisper-small-jp/resolve/main/ct2/tokenizer.json
3.93 MB
File too large to display, you can check the raw version instead.