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:
- 83e8dc6449be47ec4b989fd1d4adcdf64e35e38771dfb76c3e772d709d65aae7
- Size of remote file:
- 152 kB
- SHA256:
- f48060903ac21e0becf16dd013e88bcf638e1e19ea5db188db0e854e2bca3503
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.