Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Javanese
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use OwLim/whisper-java-SLR41-SLR35 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OwLim/whisper-java-SLR41-SLR35 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="OwLim/whisper-java-SLR41-SLR35")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("OwLim/whisper-java-SLR41-SLR35") model = AutoModelForSpeechSeq2Seq.from_pretrained("OwLim/whisper-java-SLR41-SLR35", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95dbbe3d5d5115d11217b6bcf9685ff25ae4f70102b57bd981f9faf62088613a
- Size of remote file:
- 5.5 kB
- SHA256:
- e911f80dfe49b29cafae0b5d2f8466301dfb2ff66fedaf3eea73f97d28cf0535
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