Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Javanese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use OwLim/whisper-java-SLR41 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OwLim/whisper-java-SLR41 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="OwLim/whisper-java-SLR41")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("OwLim/whisper-java-SLR41") model = AutoModelForSpeechSeq2Seq.from_pretrained("OwLim/whisper-java-SLR41") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7055bf1e717762e20994b3ff523c0d7abff19be007a9c52d65b8619527818aaf
- Size of remote file:
- 5.43 kB
- SHA256:
- 9f32365c3a6005dc74e928d40a39cade64009ba84f2b5deada8fecbf709485e2
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