Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-small-sr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-small-sr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-small-sr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-small-sr") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-small-sr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 233a54f372ae7c8fa10d5c8ca1d1aef0b784662bec0dda84a4b14b4b42323a6b
- Size of remote file:
- 4.22 kB
- SHA256:
- 283406f05753626382783c4fd477551e5c475e27dc77ced25335e61e703d63ea
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