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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51c0b1e6273b72d117827cf03b4bbe42099e8a1c62b0ff108c5fddce5018070f
- Size of remote file:
- 967 MB
- SHA256:
- 2c472a2a72b54f95506fabf0d5a4e4b25609ffd28405d5a2cdde1b625c630174
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