Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Turkish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use notlober/whisper-large-en-tr-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notlober/whisper-large-en-tr-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="notlober/whisper-large-en-tr-multi")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("notlober/whisper-large-en-tr-multi") model = AutoModelForMultimodalLM.from_pretrained("notlober/whisper-large-en-tr-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13d114ed348631a967e047c9da4ba3f5c7043e34f2b1966122f22f3e3fe8426b
- Size of remote file:
- 1.18 GB
- SHA256:
- 92ea5b148f91b720c54bd9fd250bef56238b57c36c140135e38855c5832518fb
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