Instructions to use OpenSound/CapSpeech-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenSound/CapSpeech-models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="OpenSound/CapSpeech-models")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenSound/CapSpeech-models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ar_CapTTS-SE/generation_config.json from OpenSound/CapSpeech-models: direct link, hf CLI and curl.
- Browser
- Download file 265 Bytes
-
https://huggingface.co/OpenSound/CapSpeech-models/resolve/refs%2Fpr%2F2/ar_CapTTS-SE/generation_config.json
- Command line
-
hf download hf://OpenSound/CapSpeech-models@refs/pr/2/ar_CapTTS-SE/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/OpenSound/CapSpeech-models/resolve/refs%2Fpr%2F2/ar_CapTTS-SE/generation_config.json
265 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1025, | |
| "decoder_start_token_id": 1025, | |
| "do_sample": true, | |
| "eos_token_id": 1024, | |
| "guidance_scale": 1, | |
| "max_length": 2580, | |
| "min_new_tokens": 10, | |
| "pad_token_id": 1024, | |
| "transformers_version": "4.46.1" | |
| } | |