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 AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("sesame/csm-1b") model = AutoModelForTextToWaveform.from_pretrained("sesame/csm-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
#47
by dylanebert - opened
No description provided.
Hey @eustlb do you know who we can ping to get this merged?
This will help us with discovery on providing support for such models on Azure AI, as in having a clear way to determine whether a model is supported on Transformers or not, thanks in advance 🤗
Zackh changed pull request status to closed