Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
whisper
speech-recognition
multilingual
Instructions to use Svetozar1993/MultilingualSTT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svetozar1993/MultilingualSTT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Svetozar1993/MultilingualSTT")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Svetozar1993/MultilingualSTT") model = AutoModelForSpeechSeq2Seq.from_pretrained("Svetozar1993/MultilingualSTT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- add618babb273b8b3b7eb293f72ad8e41f4e741d78f4ebf4e47f6c35b8d2ea8d
- Size of remote file:
- 6.17 GB
- SHA256:
- e9c7b745947df8856bb809974ac7f9ef2704f7834ab1760fc925f38f8f5517f5
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