Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Indonesian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use TheRains/cv9-special-batch12-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheRains/cv9-special-batch12-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheRains/cv9-special-batch12-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheRains/cv9-special-batch12-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheRains/cv9-special-batch12-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfc25ddbf5188333ae9dc0440f8df48ad6da6c23adfc4afd46d61af50d3ae06d
- Size of remote file:
- 4.16 kB
- SHA256:
- a5f81fb9470ca9dabfddc2f5589a5235548bdc47242e7b40c4a1031aef362d64
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.