Instructions to use drbaph/LongCat-AudioDiT-3.5B-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drbaph/LongCat-AudioDiT-3.5B-bf16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="drbaph/LongCat-AudioDiT-3.5B-bf16")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("drbaph/LongCat-AudioDiT-3.5B-bf16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44c7bcec5c104af849974b7d76f29b502e3d9d0cfad2d24c7461bebe2d3a9345
- Size of remote file:
- 7.67 GB
- SHA256:
- dd3beb8dd0b7c3e9b221168bcd92497cfcafe5e546ca68501dfc51f5d012f947
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