Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use iqbalasrif/whisper-tiny-hyperparameter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iqbalasrif/whisper-tiny-hyperparameter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="iqbalasrif/whisper-tiny-hyperparameter")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("iqbalasrif/whisper-tiny-hyperparameter") model = AutoModelForSpeechSeq2Seq.from_pretrained("iqbalasrif/whisper-tiny-hyperparameter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53d3ea51a8f0a50f03da7fc592393f1712fa800770ee2a23e57902e4482dc5e1
- Size of remote file:
- 151 MB
- SHA256:
- 5205c7a053754888cd2d7c413fb555b938a6a92aa1057c89b9d7231641cceb69
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