Automatic Speech Recognition
Transformers
PyTorch
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-medium-sr-fleurs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-medium-sr-fleurs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-medium-sr-fleurs")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-medium-sr-fleurs") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-medium-sr-fleurs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1479ba3195ec76226dbc20df7cc37c2a561672be4ea352ec23eeb394dc8cd160
- Size of remote file:
- 4.22 kB
- SHA256:
- 7651e7d92bf88d45d6c9bd2873a9ec6d82a65498c057801e5deb891a08e1ac4d
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