Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sercan/whisper-small-cv-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sercan/whisper-small-cv-tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sercan/whisper-small-cv-tr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sercan/whisper-small-cv-tr") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sercan/whisper-small-cv-tr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3311a1ad18542ef63c547fd10d1348ffa99a0688ea525e770fceb59d78e456d2
- Size of remote file:
- 967 MB
- SHA256:
- 4e8a1e0103bcbb269e85ee6f48a5658e543a4e147d032e305763223390ebaf92
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