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: 549 Bytes
c92b425 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | {
"architectures": [
"SpeechT5HifiGan"
],
"dtype": "float32",
"initializer_range": 0.01,
"leaky_relu_slope": 0.1,
"model_in_dim": 8,
"model_type": "hifigan",
"normalize_before": false,
"resblock_dilation_sizes": [
[
1,
3,
5
],
[
1,
3,
5
]
],
"resblock_kernel_sizes": [
3,
7
],
"sampling_rate": 16000,
"transformers_version": "4.57.1",
"upsample_initial_channel": 16,
"upsample_kernel_sizes": [
4,
4
],
"upsample_rates": [
2,
2
]
}
|