Instructions to use AlanRobotics/whisper-tiny-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/whisper-tiny-ru with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AlanRobotics/whisper-tiny-ru")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("AlanRobotics/whisper-tiny-ru") model = AutoModelForSpeechSeq2Seq.from_pretrained("AlanRobotics/whisper-tiny-ru") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68513e220747352db123ea2b59520783e5e35c9a121402b26eedc8de6cfb44db
- Size of remote file:
- 4.16 kB
- SHA256:
- 207cbd4211a5ec3e8368e4bc657c3e078d13c3f8c32c72a6c515cccaa5fe418f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.