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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19ec2601aabb20b9d814adcfc79d03a39442f5e2b3a846a9c6a6cb9b6877db28
- Size of remote file:
- 3.09 GB
- SHA256:
- 8f3dd0108a56caf505b47740a385a6f61be03e670f4fc34e21e3d2bc98d7b6d1
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