Instructions to use codewithdark/csm-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/csm-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="codewithdark/csm-1b")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("codewithdark/csm-1b") model = AutoModelForTextToWaveform.from_pretrained("codewithdark/csm-1b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5f30c232a112cc863aeee5082c90cf3150e16e2ee81af55ad9f1bae5243866a
- Size of remote file:
- 5.78 kB
- SHA256:
- b116f1f603c0d482b6f1dcf37853729474d4967f9ec6e2837dc2e4c12d307c30
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