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
| """ | |
| Dataset Handler | |
| Handles dataset import and exploration functionality | |
| """ | |
| from typing import Optional, Tuple, Any, Dict | |
| class DatasetHandler: | |
| """Dataset Handler for Dataset Explorer functionality""" | |
| def __init__(self): | |
| """Initialize dataset handler""" | |
| self.dataset = None | |
| self.dataset_imported = False | |
| def import_dataset(self, dataset_type: str) -> str: | |
| """ | |
| Import dataset (temporarily disabled) | |
| Args: | |
| dataset_type: Type of dataset to import (e.g., "train", "test") | |
| Returns: | |
| Status message string | |
| """ | |
| self.dataset_imported = False | |
| return f"⚠️ Dataset import is currently disabled. Text2MusicDataset dependency not available." | |
| def get_item_data(self, *args, **kwargs) -> Tuple: | |
| """ | |
| Get dataset item (temporarily disabled) | |
| Returns: | |
| Tuple of placeholder values matching the expected return format | |
| """ | |
| return "", "", "", "", "", None, None, None, "❌ Dataset not available", "", 0, "", None, None, None, {}, "text2music" | |