Instructions to use niobures/AudioLDM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use niobures/AudioLDM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("niobures/AudioLDM", 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 code/AudioLDM-training-finetuning.zip from niobures/AudioLDM: direct link, hf CLI and curl.
- Browser
- Download file 3.55 MB
-
https://huggingface.co/niobures/AudioLDM/resolve/main/code/AudioLDM-training-finetuning.zip
- Command line
-
hf download hf://niobures/AudioLDM/code/AudioLDM-training-finetuning.zip
-
curl -L -o AudioLDM-training-finetuning.zip https://huggingface.co/niobures/AudioLDM/resolve/main/code/AudioLDM-training-finetuning.zip
3.55 MB
- Xet hash:
- 0173348f5f67b2a5a9bb9d21b840aa961c23dcdfe4c33d1adb54af4525500d30
- Size of remote file:
- 3.55 MB
- SHA256:
- 8d840322e5fdd7504cb2646860046c85f3af9c1b1bc91747d739e5642da638e5
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