Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-large-v3-sr-combined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-large-v3-sr-combined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-large-v3-sr-combined")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-large-v3-sr-combined") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-large-v3-sr-combined") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14eb46a9f36d1253190c20e4c7f7061296eec551d0d1a13b05c8c15d6b508e09
- Size of remote file:
- 4.28 kB
- SHA256:
- 9efb9cd7be014a599eede158a8dded763817dcab3b04cd3052980af7f6e3e3e3
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