Instructions to use kimbochen/whisper-tiny-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kimbochen/whisper-tiny-ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kimbochen/whisper-tiny-ja")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kimbochen/whisper-tiny-ja") model = AutoModelForSpeechSeq2Seq.from_pretrained("kimbochen/whisper-tiny-ja") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8c5af75e6e1b64e2e81b5468752844934f339d7b7df828854b5ffe9261346914
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size 151061672
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