Text-to-Audio
Transformers
Safetensors
qadit
feature-extraction
diffusion
dit
audio
educational
research
custom_code
Instructions to use QuarkML/QaDiT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuarkML/QaDiT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="QuarkML/QaDiT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QuarkML/QaDiT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 444 Bytes
3e0b0bf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | """QaDiT Hugging Face Transformers package (trust_remote_code)."""
from .configuration_qadit import QaDiTConfig
from .modelling_qadit import (
QaDiTGeneratorOutput,
QaDiTModel,
QaDiTOutput,
)
try:
from .processing_qadit import QaDiTProcessor
except Exception: # optional helper
QaDiTProcessor = None
__all__ = [
"QaDiTConfig",
"QaDiTModel",
"QaDiTOutput",
"QaDiTGeneratorOutput",
"QaDiTProcessor",
]
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