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:
- efdf1f7c9bf89b482d9da2d320ae810be45eaa42f83b540aa67d5d028295e27e
- Size of remote file:
- 5.3 kB
- SHA256:
- 399241e1b2b8a49e752b4e5f4e9c569210a09ec06e1436a7271d2b85470fed4f
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