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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from khmerttsopensource/khmer-tts: direct link, hf CLI and curl.
- Browser
- Download file 254 Bytes
-
https://huggingface.co/khmerttsopensource/khmer-tts/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://khmerttsopensource/khmer-tts/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/khmerttsopensource/khmer-tts/resolve/main/preprocessor_config.json
254 Bytes
| { | |
| "feature_extractor_type": "VitsFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 256, | |
| "max_wav_value": 32768.0, | |
| "n_fft": 1024, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |