Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Javanese
whisper
javanese
asr
Generated from Trainer
Eval Results (legacy)
Instructions to use bagasshw/asr_java_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bagasshw/asr_java_result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bagasshw/asr_java_result")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bagasshw/asr_java_result") model = AutoModelForSpeechSeq2Seq.from_pretrained("bagasshw/asr_java_result") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff1f69801c94132ff1d5418269a68c297275e74e6fe63fb0c9f5dfb0713ab2b4
- Size of remote file:
- 151 MB
- SHA256:
- 317de81a7fe522dcf7dca1c18d0896298bbb7b47f806da81ea728aa37df3d332
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