Instructions to use sesame/csm-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sesame/csm-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="sesame/csm-1b")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("sesame/csm-1b") model = AutoModelForTextToWaveform.from_pretrained("sesame/csm-1b") - Notebooks
- Google Colab
- Kaggle
Request: DOI
#17
by zhoupfpf - opened