Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Indonesian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use evanarlian/whisper-base-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evanarlian/whisper-base-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="evanarlian/whisper-base-id")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("evanarlian/whisper-base-id") model = AutoModelForSpeechSeq2Seq.from_pretrained("evanarlian/whisper-base-id") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9c73041acba8932027ee8b3b0e860ba97d1d112c5df6c152d6e05e908c8fa15
- Size of remote file:
- 3.64 kB
- SHA256:
- 97f956e14f168ac86e9d91504fdde99e8229050765ba81e248c4eb53ba983573
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.