Instructions to use kosamit/whisper-tiny-ja-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kosamit/whisper-tiny-ja-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kosamit/whisper-tiny-ja-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kosamit/whisper-tiny-ja-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("kosamit/whisper-tiny-ja-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kosamit/whisper-tiny-ja-test: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/kosamit/whisper-tiny-ja-test/resolve/main/training_args.bin
- Command line
-
hf download hf://kosamit/whisper-tiny-ja-test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kosamit/whisper-tiny-ja-test/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- ab658ebc00c8b866392b39be225d0f976e43e873326cf7bb36047b83f7a68073
- Size of remote file:
- 4.66 kB
- SHA256:
- db8b5f32ad54b8ecc31939465018a68babc671097759ecf40ece4a4d14fbd956
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