Instructions to use khmerttsopensource/khmer-tts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khmerttsopensource/khmer-tts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="khmerttsopensource/khmer-tts")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("khmerttsopensource/khmer-tts") model = AutoModelForPreTraining.from_pretrained("khmerttsopensource/khmer-tts") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 980f062278656ecedc2f6e0934a6987d17cd02b6f1b6141e4b1e7861b9ee22e2
- Size of remote file:
- 101 kB
- SHA256:
- cc49f4ac3432e5faa3fe7c3070e77fb5c07d3b6861ec27c3fa79fbaa0d714d8e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.