Instructions to use TTS-AGI/ACE-Step-1.5-Backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TTS-AGI/ACE-Step-1.5-Backup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TTS-AGI/ACE-Step-1.5-Backup", 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
Download code/.env.example from TTS-AGI/ACE-Step-1.5-Backup: direct link, hf CLI and curl.
- Browser
- Download file 123 Bytes
-
https://huggingface.co/TTS-AGI/ACE-Step-1.5-Backup/resolve/main/code/.env.example
- Command line
-
hf download hf://TTS-AGI/ACE-Step-1.5-Backup/code/.env.example
-
curl -L -o .env.example https://huggingface.co/TTS-AGI/ACE-Step-1.5-Backup/resolve/main/code/.env.example
123 Bytes
| ACESTEP_CONFIG_PATH=acestep-v15-turbo | |
| ACESTEP_LM_MODEL_PATH=acestep-5Hz-lm-1.7B | |
| ACESTEP_DEVICE=auto | |
| ACESTEP_LM_BACKEND=vllm |