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", torch_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
| set -euo pipefail | |
| ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" | |
| CONDA_ACTIVATE="${CONDA_ACTIVATE:-/root/data/repo/gongjunmin/miniconda3/bin/activate}" | |
| CONDA_ENV_NAME="${ACESTEP_CONDA_ENV:-acestep_v15_train}" | |
| HOST="${ACESTEP_API_HOST:-0.0.0.0}" | |
| PORT="${ACESTEP_API_PORT:-8001}" | |
| LOG_LEVEL="${ACESTEP_API_LOG_LEVEL:-debug}" | |
| cd "$ROOT_DIR" | |
| # 临时关闭 nounset 以避免 conda activate.d 脚本中的 unbound variable 错误 | |
| set +u | |
| # shellcheck disable=SC1090 | |
| source "$CONDA_ACTIVATE" "$CONDA_ENV_NAME" | |
| set -u | |
| # NOTE: api_server 使用内存队列/任务存储,要求 workers=1。 | |
| nohup python -m uvicorn acestep.api_server:app \ | |
| --host "0.0.0.0" \ | |
| --port "8001" \ | |
| --workers 1 \ | |
| --log-level "$LOG_LEVEL" > server.log 2>&1 & | |
| echo "Server started in background with PID $!. Logs in server.log" |