Instructions to use lsnoo/russian_fairseq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsnoo/russian_fairseq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lsnoo/russian_fairseq")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lsnoo/russian_fairseq") model = AutoModelForCTC.from_pretrained("lsnoo/russian_fairseq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc62235342e125aad4d3fb436f9bf6ef3b6462afe788ca6b3c73d8c71918c279
- Size of remote file:
- 1.26 GB
- SHA256:
- 30e156668157d8234bf84558dcc5554b339233e8dfac4eabf34d58c1fcd079ce
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