Instructions to use KBLab/wav2vec2-large-voxrex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/wav2vec2-large-voxrex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KBLab/wav2vec2-large-voxrex")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("KBLab/wav2vec2-large-voxrex") model = AutoModelForPreTraining.from_pretrained("KBLab/wav2vec2-large-voxrex") - Notebooks
- Google Colab
- Kaggle
Updated to version C
Browse files- README.md +3 -2
- pytorch_model.bin +1 -1
README.md
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license: cc0
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# Wav2vec 2.0 large VoxRex (
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**Disclaimer:** This is a work in progress.
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This model has been pretrained for
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license: cc0
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# Wav2vec 2.0 large VoxRex (C)
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**Disclaimer:** This is a work in progress.
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**Update 2022-01-08:** Updated to VoxRex-C version, use git to get the older (B) version
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This model has been pretrained for 400,000 updates on the P4-10k corpus which contains 10 000 hours of swedish local public service radio as well as 1500 hours of audio books and other speech from KBs collections.
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