Instructions to use facebook/mms-tts-uig-script_arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-tts-uig-script_arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="facebook/mms-tts-uig-script_arabic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-uig-script_arabic") model = AutoModelForTextToWaveform.from_pretrained("facebook/mms-tts-uig-script_arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from facebook/mms-tts-uig-script_arabic: direct link, hf CLI and curl.
- Browser
- Download file 254 Bytes
-
https://huggingface.co/facebook/mms-tts-uig-script_arabic/resolve/refs%2Fpr%2F2/preprocessor_config.json
- Command line
-
hf download hf://facebook/mms-tts-uig-script_arabic@refs/pr/2/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/facebook/mms-tts-uig-script_arabic/resolve/refs%2Fpr%2F2/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": 22050 | |
| } | |