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:
- 2de5098f456c835b6c813b0fd66e9d2292b976c14627dfda2f11e0f0c20f658d
- Size of remote file:
- 1.18 GB
- SHA256:
- 81f7081b28d17e0ed1900c8d8b63c507f9671e8bbaec781c45b3d0f1266b1efd
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