Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-tiny-sr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-tiny-sr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-tiny-sr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-tiny-sr") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-tiny-sr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b74c7b8d698f4f7beb78de98e99b0e420ac4c613a22232211acf4aa6c5ce227
- Size of remote file:
- 5.11 kB
- SHA256:
- 57c41f290ab4824cef3265b32d1d37fdebc19ed697290b50594bd27ad7084ad8
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