Instructions to use keanteng/sesame-csm-elise-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keanteng/sesame-csm-elise-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="keanteng/sesame-csm-elise-lora")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("keanteng/sesame-csm-elise-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0535087d72e6305d3c1bf2c79c79ca7638b497d777b91af49149eb975d0e6d11
- Size of remote file:
- 480 kB
- SHA256:
- 152aa1aec68589c27f5e3311e1ecf375daaf5704aa17ef3d19d8cf1a91828b00
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