Instructions to use reazon-research/japanese-hubert-base-k2-rs35kh-bpe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reazon-research/japanese-hubert-base-k2-rs35kh-bpe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="reazon-research/japanese-hubert-base-k2-rs35kh-bpe")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("reazon-research/japanese-hubert-base-k2-rs35kh-bpe") model = AutoModelForCTC.from_pretrained("reazon-research/japanese-hubert-base-k2-rs35kh-bpe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3ec26ca85714f50a070522a0b312d51e482640d925ec2da1d3ed383c72fca64
- Size of remote file:
- 387 MB
- SHA256:
- 1bea14c303e52f441be86c1cfcf41cbb85d1631217fcf02c011455ed906d4b2b
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