Instructions to use drepic/whisper-medium-jp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drepic/whisper-medium-jp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="drepic/whisper-medium-jp")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("drepic/whisper-medium-jp") model = AutoModelForSpeechSeq2Seq.from_pretrained("drepic/whisper-medium-jp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download accelerate_state/optimizer.bin from drepic/whisper-medium-jp: direct link, hf CLI and curl.
- Browser
- Download file 76 MB
-
https://huggingface.co/drepic/whisper-medium-jp/resolve/main/accelerate_state/optimizer.bin
- Command line
-
hf download hf://drepic/whisper-medium-jp/accelerate_state/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/drepic/whisper-medium-jp/resolve/main/accelerate_state/optimizer.bin
76 MB
- Xet hash:
- 4e63c034f7b313a055bc9db71e7d09a1a6e6c2c5a97b66f58c319ec8a1610000
- Size of remote file:
- 76 MB
- SHA256:
- 2ff8cfa162c38e1f9402bb7796c7c0c95734ba612c8587cdf0e0008e8499019f
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