Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Mehtap/base_12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehtap/base_12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mehtap/base_12")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mehtap/base_12") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mehtap/base_12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad757353ac2dee55168bfef5c89c643c8755e58f10807410d8a05d2d39515d64
- Size of remote file:
- 290 MB
- SHA256:
- 250fb0986cddce21cf3ab427938398fd00c9d34215eb4df05967d08fc870eee4
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