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 models/acestep-captioner/tokenizer.json from TTS-AGI/ACE-Step-1.5-Backup: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/TTS-AGI/ACE-Step-1.5-Backup/resolve/main/models/acestep-captioner/tokenizer.json
- Command line
-
hf download hf://TTS-AGI/ACE-Step-1.5-Backup/models/acestep-captioner/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TTS-AGI/ACE-Step-1.5-Backup/resolve/main/models/acestep-captioner/tokenizer.json
11.4 MB
- Xet hash:
- c38861918c23af9030c7cfd8daefca315dc8e0fde29740104d391c2360e69753
- Size of remote file:
- 11.4 MB
- SHA256:
- 8441917e39ae0244e06d704b95b3124795cec478e297f9afac39ba670d7e9d99
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