Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Japanese
wav2vec2
common-voice
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Instructions to use vumichien/wav2vec2-xls-r-1b-japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/wav2vec2-xls-r-1b-japanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vumichien/wav2vec2-xls-r-1b-japanese")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("vumichien/wav2vec2-xls-r-1b-japanese") model = AutoModelForCTC.from_pretrained("vumichien/wav2vec2-xls-r-1b-japanese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61f98ef392df91d4c16904bbf3f3bca3c4e06d4848833fcb8d3f4071629b9849
- Size of remote file:
- 1.02 GB
- SHA256:
- d8a0984c38f72fc70fd57d13ac3b01f6f390d0373f5d598665daa596ea1251c7
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