Instructions to use hf-internal-testing/tiny-AudioLDM2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-AudioLDM2Pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-AudioLDM2Pipeline", 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
| { | |
| "_class_name": "AudioLDM2ProjectionModel", | |
| "_diffusers_version": "0.39.0.dev0", | |
| "langauge_model_dim": 16, | |
| "max_seq_length": null, | |
| "text_encoder_1_dim": 32, | |
| "text_encoder_dim": 16, | |
| "use_learned_position_embedding": null | |
| } | |