Text-to-Audio
Transformers
Diffusers
Safetensors
ACE-Step
feature-extraction
audio
music
text2music
custom_code
Instructions to use diskrot/Ace-Step1.5-diskrot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diskrot/Ace-Step1.5-diskrot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="diskrot/Ace-Step1.5-diskrot", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("diskrot/Ace-Step1.5-diskrot", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "AutoencoderOobleck", | |
| "_diffusers_version": "0.34.0", | |
| "_name_or_path": "/root/data/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 | |
| } | |