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:
- 0327ede2f81517ada1b7859a649cdf0bd145fd1a903e20857abc62499ca717e7
- Size of remote file:
- 967 MB
- SHA256:
- e31b327d6d9568747d4be3aad10af061b77f2957b997fae8cdaf44be4e0bffc0
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