Instructions to use ACE-Step/acestep-captioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ACE-Step/acestep-captioner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="ACE-Step/acestep-captioner")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("ACE-Step/acestep-captioner") model = AutoModelForTextToWaveform.from_pretrained("ACE-Step/acestep-captioner") - Notebooks
- Google Colab
- Kaggle
| model-00005-of-00005.safetensors | |
| config.json | |
| spk_dict.pt | |
| video_preprocessor_config.json | |
| model-00004-of-00005.safetensors | |
| vocab.json | |
| tokenizer_config.json | |
| chat_template.jinja | |
| model-00002-of-00005.safetensors | |
| model.safetensors.index.json | |
| model-00003-of-00005.safetensors | |
| model-00001-of-00005.safetensors | |
| special_tokens_map.json | |
| added_tokens.json | |
| tokenizer.json | |
| generation_config.json | |
| preprocessor_config.json | |
| merges.txt | |
| args.json | |
| deploy_result/20250825-143105.jsonl | |
| deploy_result/20250825-141923.jsonl | |
| deploy_result/20250827-025556.jsonl | |