Instructions to use reazon-research/japanese-wav2vec2-large-rs35kh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reazon-research/japanese-wav2vec2-large-rs35kh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="reazon-research/japanese-wav2vec2-large-rs35kh")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("reazon-research/japanese-wav2vec2-large-rs35kh") model = AutoModelForCTC.from_pretrained("reazon-research/japanese-wav2vec2-large-rs35kh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94546ea6d25af7b95cbb455e579900b025798bc67ba3234abbb5b49ed3dabc2e
- Size of remote file:
- 1.27 GB
- SHA256:
- cc0228dfe1d939e541624c78911eafc7041698e1b2f4853de8a6364fb4557364
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.