Instructions to use drbaph/LongCat-AudioDiT-3.5B-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drbaph/LongCat-AudioDiT-3.5B-fp8 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-fp8")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("drbaph/LongCat-AudioDiT-3.5B-fp8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b51baf2c7e33268756816cc1df72bf62224974253d991811dfeca31fcb8ddb38
- Size of remote file:
- 3.84 GB
- SHA256:
- 07dbc962ceae00333505c1daf649e4bd15709168f7295cc01bd750813c193085
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