Instructions to use cvssp/audioldm-l-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cvssp/audioldm-l-full 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/audioldm-l-full", 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
Audio conditioning option in the difference between audioldm-m-full and audioldm-l-full
#2
by maxin-cn - opened
Thank you for your wonderful work. I'm curious that there is an audio conditioning option in the difference between audioldm-m-full and audioldm-l-full. What does this audio conditioning refer to specifically, is it the condition of the CLAP audio embedding as a model in the paper?