Automatic Speech Recognition
Transformers
PyTorch
Turkish
wav2vec2
common_voice
Generated from Trainer
Instructions to use cahya/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cahya/output")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("cahya/output") model = AutoModelForCTC.from_pretrained("cahya/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75dba81d6a0741b7b9ee1d97fcbf8e0199d7c0cfcc87c806e222401aa1fd7305
- Size of remote file:
- 378 MB
- SHA256:
- 826c9581894060d5018f53f31392e85a02d39f39b95f426391253a630e20d320
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