Text-to-Audio
Diffusers
Safetensors
ACE-Step
AceStepPipeline
audio
music
text-to-music
flow-matching
Instructions to use ACE-Step/acestep-v15-xl-base-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ACE-Step/acestep-v15-xl-base-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ACE-Step/acestep-v15-xl-base-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - ACE-Step
How to use ACE-Step/acestep-v15-xl-base-diffusers with ACE-Step:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 438 Bytes
05791af | 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 | {
"_class_name": "AutoencoderOobleck",
"_diffusers_version": "0.38.0.dev0",
"_name_or_path": "/vepfs-d-data/q-ace/repo/gongjunmin/ACE-Step-1.5/checkpoints/vae",
"audio_channels": 2,
"channel_multiples": [
1,
2,
4,
8,
16
],
"decoder_channels": 128,
"decoder_input_channels": 64,
"downsampling_ratios": [
2,
4,
4,
6,
10
],
"encoder_hidden_size": 128,
"sampling_rate": 48000
}
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