Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-large-v3-sr-cmb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-large-v3-sr-cmb 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-cmb")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-large-v3-sr-cmb") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-large-v3-sr-cmb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e96b87c298b6f82194d3bc9d475ece2d4dc509a3cc06bb3315a1db5b7f08faa1
- Size of remote file:
- 4.28 kB
- SHA256:
- 463f40356611d99571748462146422e1a1342b4828fb799c797d7d15be4c5735
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