Instructions to use AlanRobotics/whisper-small-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/whisper-small-ru with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AlanRobotics/whisper-small-ru")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("AlanRobotics/whisper-small-ru") model = AutoModelForSpeechSeq2Seq.from_pretrained("AlanRobotics/whisper-small-ru") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07c7374187aa5cac241e67ab7bcdd49a5c7666635c6f21f984cb21fea4fee19c
- Size of remote file:
- 967 MB
- SHA256:
- 3871e1949fa9e7bc1dfb89d2bffac1329cc92213750a47113272952f913716ac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.