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:
- 66337095def25e733d8fd33fa22a1898ee7a7d16a81cb5f026db2f3aec992c10
- Size of remote file:
- 122 kB
- SHA256:
- 5aa350b3a7e9620b420de41a9ccbf16bdbbb25dcfcf63a8ae11b12537ba05d7c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.