Instructions to use bond005/whisper-large-v3-ru-podlodka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bond005/whisper-large-v3-ru-podlodka with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bond005/whisper-large-v3-ru-podlodka")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bond005/whisper-large-v3-ru-podlodka") model = AutoModelForSpeechSeq2Seq.from_pretrained("bond005/whisper-large-v3-ru-podlodka", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff319ea9fe140be777791c80542f3dfa6ff3c719f3bfc6fd1aca755c458474b6
- Size of remote file:
- 4.99 GB
- SHA256:
- 7bb39d59f810cc5c013885ea6fe371ad19eea5bbce2e47e07b2465b8721d8af0
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