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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79d1eb8693f8710da64726c5a651ce11f378aa1a40e6625fc0b5e53f8574fe43
- Size of remote file:
- 5.5 kB
- SHA256:
- 37dfedf9d0e27bcfda147c1014d1350fcfb6281cacd8f153a384e1910d896d71
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