Instructions to use MarcNg/onnx-fastspeech2-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarcNg/onnx-fastspeech2-vi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MarcNg/onnx-fastspeech2-vi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("MarcNg/onnx-fastspeech2-vi") model = AutoModelForSpeechSeq2Seq.from_pretrained("MarcNg/onnx-fastspeech2-vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe1409ec80ffc1d61e481f8aacca813da1ba9d16168e7d93454030f6e027ba7d
- Size of remote file:
- 31 MB
- SHA256:
- 2ebdd891de60be6e0a8d5f4e366679af29aed3fc4bdaf7d92e48085ce4cf3f4c
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