Instructions to use Runware/acestep-v15-xl-base-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/acestep-v15-xl-base-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/acestep-v15-xl-base-diffusers", 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
File size: 1,303 Bytes
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"_class_name": "AceStepTransformer1DModel",
"_diffusers_version": "0.39.0.dev0",
"attention_bias": false,
"attention_dropout": 0.0,
"audio_acoustic_hidden_dim": 64,
"encoder_hidden_size": 2048,
"head_dim": 128,
"hidden_size": 2560,
"in_channels": 192,
"intermediate_size": 9728,
"is_turbo": false,
"layer_types": [
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention",
"sliding_attention",
"full_attention"
],
"model_version": "base",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"patch_size": 2,
"rms_norm_eps": 1e-06,
"rope_theta": 1000000,
"sliding_window": 128
}
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