Text-to-Audio
Transformers
Safetensors
qadit
feature-extraction
diffusion
dit
audio
educational
research
custom_code
Instructions to use QuarkML/QaDiT-160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuarkML/QaDiT-160 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="QuarkML/QaDiT-160", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QuarkML/QaDiT-160", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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import torch
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model = AutoModel.from_pretrained(
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trust_remote_code=True,
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).to("cuda" if torch.cuda.is_available() else "cpu")
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import torch
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model = AutoModel.from_pretrained(
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"QuarkML/QaDiT", # or a local export folder
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trust_remote_code=True,
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).to("cuda" if torch.cuda.is_available() else "cpu")
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