Instructions to use demo-time/kevin-conroy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use demo-time/kevin-conroy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="demo-time/kevin-conroy")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("demo-time/kevin-conroy") model = AutoModelForTextToWaveform.from_pretrained("demo-time/kevin-conroy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download preprocessor_config.json from demo-time/kevin-conroy: direct link, hf CLI and curl.
- Browser
- Download file 271 Bytes
-
https://huggingface.co/demo-time/kevin-conroy/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://demo-time/kevin-conroy/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/demo-time/kevin-conroy/resolve/main/preprocessor_config.json
271 Bytes
| { | |
| "chunk_length_s": null, | |
| "feature_extractor_type": "EncodecFeatureExtractor", | |
| "feature_size": 1, | |
| "overlap": null, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "CsmProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 24000 | |
| } | |