Instructions to use cvssp/audioldm2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cvssp/audioldm2-large 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-large", 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 text_encoder_2/pytorch_model.bin from cvssp/audioldm2-large: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/cvssp/audioldm2-large/resolve/main/text_encoder_2/pytorch_model.bin
- Command line
-
hf download hf://cvssp/audioldm2-large/text_encoder_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cvssp/audioldm2-large/resolve/main/text_encoder_2/pytorch_model.bin
1.36 GB
- Xet hash:
- cdde072d600ade0bca049ea4b1245ce71e41a0223c4c303744d17081a760c87b
- Size of remote file:
- 1.36 GB
- SHA256:
- 8c4be8e23954ef72bd0d623206a46b7e1ab7fa23f530b7b9f691d40785273b27
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