Instructions to use cvssp/audioldm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cvssp/audioldm2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cvssp/audioldm2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download projection_model/diffusion_pytorch_model.bin from cvssp/audioldm2: direct link, hf CLI and curl.
- Browser
- Download file 4.74 MB
-
https://huggingface.co/cvssp/audioldm2/resolve/main/projection_model/diffusion_pytorch_model.bin
- Command line
-
hf download hf://cvssp/audioldm2/projection_model/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/cvssp/audioldm2/resolve/main/projection_model/diffusion_pytorch_model.bin
4.74 MB
- Xet hash:
- 17066aaa6df972c2be07241da0b71b45860c0640e55883a39a1a486d2e78d9e9
- Size of remote file:
- 4.74 MB
- SHA256:
- cfb555ca6f1d76278436c48bafea78b5122b9496434694cb8866c096fb1c6ad0
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