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: 919 Bytes
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"architectures": [
"QaDiTModel"
],
"auto_map": {
"AutoConfig": "configuration_qadit.QaDiTConfig",
"AutoModel": "modelling_qadit.QaDiTModel"
},
"depth": 12,
"dtype": "float32",
"guidance_scale": 4.0,
"hidden_size": 768,
"latent_channels": 8,
"latent_freq": 16,
"latent_scale": 0.9503493000009796,
"latent_time": 256,
"load_auxiliaries": true,
"logit_normal_mean": 0.0,
"logit_normal_std": 1.0,
"mlp_ratio": 4.0,
"model_type": "qadit",
"num_heads": 12,
"num_inference_steps": 50,
"num_train_timesteps": 1000,
"patch_size": 2,
"repa_layer": 4,
"sample_rate": 16000,
"schedule": "cosine",
"text_dim": 1024,
"text_max_length": 64,
"text_model": "google/flan-t5-large",
"transformers_version": "5.14.1",
"vae_model": "cvssp/audioldm-s-full-v2",
"vae_subfolder": "vae",
"vocoder_model": "cvssp/audioldm-s-full-v2",
"vocoder_subfolder": "vocoder"
}
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