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
File size: 237 Bytes
c92b425 | 1 2 3 4 5 6 7 8 9 10 | {
"_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
}
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