Instructions to use bond005/whisper-large-v2-ru-podlodka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bond005/whisper-large-v2-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-v2-ru-podlodka")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bond005/whisper-large-v2-ru-podlodka") model = AutoModelForSpeechSeq2Seq.from_pretrained("bond005/whisper-large-v2-ru-podlodka", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bond005/whisper-large-v2-ru-podlodka: direct link, hf CLI and curl.
- Browser
- Download file 2.2 MB
-
https://huggingface.co/bond005/whisper-large-v2-ru-podlodka/resolve/main/tokenizer.json
- Command line
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hf download hf://bond005/whisper-large-v2-ru-podlodka/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/bond005/whisper-large-v2-ru-podlodka/resolve/main/tokenizer.json
2.2 MB
File too large to display, you can check the raw version instead.